{ "data": { "a": { "slug": "agentcore-memory", "name": "Amazon Bedrock AgentCore Memory", "vendor": "Amazon Web Services", "vendorUrl": "https://aws.amazon.com/bedrock/agentcore/", "kind": "http-api", "category": "agent-memory", "summary": "Managed memory service for AI agents on AWS. It stores conversation events as short-term memory and extracts facts, preferences, summaries and episodes into searchable long-term records, through the AWS API, SDKs and an MCP server.", "url": "https://www.anchorterminal.com/tools/agentcore-memory", "markdownUrl": "https://www.anchorterminal.com/tools/agentcore-memory.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/agentcore-memory.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/agentcore-memory.json", "dns": "agentcore-memory.grade.anchorterminal.com", "repo": "https://github.com/aws/bedrock-agentcore-sdk-python", "license": "Proprietary service under the AWS Customer Agreement and Service Terms. The `bedrock-agentcore` Python SDK and the `@aws/agentcore` CLI are Apache-2.0", "transports": [ "http", "stdio" ], "remoteUrl": "https://bedrock-agentcore.{region}.amazonaws.com", "packages": [ { "registry": "pypi", "name": "bedrock-agentcore" }, { "registry": "pypi", "name": "boto3" }, { "registry": "npm", "name": "@aws-sdk/client-bedrock-agentcore" }, { "registry": "npm", "name": "@aws/agentcore" }, { "registry": "pypi", "name": "awslabs.amazon-bedrock-agentcore-mcp-server" } ], "auth": "mixed", "authNotes": "AWS Signature Version 4 with IAM access keys or a role, and a policy that allows actions such as `bedrock-agentcore:CreateEvent` and `bedrock-agentcore:RetrieveMemoryRecords` on the memory resource. The data plane accepts SigV4 only. Resource-based policies and the condition keys `bedrock-agentcore:namespace` and `bedrock-agentcore:namespacePath` narrow access further. For end users, an AgentCore Gateway with the `agentcore-memory` connector accepts OAuth (JWT) tokens and applies Cedar policies. Access is self-serve once a person has created an AWS account.", "pricing": "usage", "pricingNotes": "Usage-priced with no minimum fee. Short-term memory, as of 6 October 2026, is $1.00 per GB ingested, $0.20 per GB retrieved and $0.10 per GB-month stored, with each event billed as at least 12 KB and at most 64 KB on ingestion and retrieval. Long-term memory is $0.75 per 1,000 records a month with built-in strategies, $0.25 with overrides or self-managed strategies (model usage is then billed in the customer's account), and $0.50 per 1,000 retrievals. No Memory-specific free tier or sandbox. New AWS accounts get up to $200 in Free Tier credits, and AWS says most new customers can sign up without a payment method (https://aws.amazon.com/bedrock/agentcore/pricing/, https://aws.amazon.com/free/free-tier-faqs/).", "priceSummary": "$1 / GB", "where": "both", "x402": { "level": "no", "evidence": "No x402, MPP or L402 on the Memory endpoints in the developer guide, the API reference or the pricing page (checked 2026-10-08). AgentCore payments is a separate AgentCore feature for an agent's own outbound payments.", "endpoints": [] }, "toolCount": 21, "popularity": { "githubStars": 776, "npmWeekly": 1070970, "pypiWeekly": null, "asOf": "2026-10-08" }, "docsUrl": "https://docs.aws.amazon.com/bedrock-agentcore/latest/devguide/memory.html", "llmsTxt": "https://docs.aws.amazon.com/bedrock-agentcore/latest/devguide/llms.txt", "capabilities": [ "memory.store", "memory.search", "memory.user", "memory.delete" ], "tags": [ "hosted", "usage-priced", "closed-source", "python", "typescript", "enterprise", "llms-txt", "free-credits", "mcp", "stdio", "namespaces", "idempotency", "soc2", "status-page" ], "lastRelease": "2026-10-30", "graded": true, "anchor": { "graded": true, "score": 79.7, "grade": "A", "agentReady": true, "rank": 17, "ranked": true, "rankOf": 1486, "categoryRank": 1, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 86, "maintenance": 83, "payments": 30, "reliability": 88, "schema": 92, "security": 87, "transparency": 79 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-01" }, "negative": 0, "verdict": "Access is IAM-controlled down to one namespace, with published per-second quotas for every operation and a `clientToken` on event writes. Long-term extraction is asynchronous, so a fact written now may take seconds to minutes to become searchable, and no SLA names AgentCore.", "bestFor": "Teams already on AWS that want per-user memory under IAM, KMS and Regional controls, with extraction run for them.", "strengths": [ "IAM permissions per operation, resource-based policies and namespace condition keys, with OAuth sign-in and deny-by-default Cedar policies available through AgentCore Gateway", "Per-second quotas published for every Memory operation, such as 200 `CreateEvent` and 30 `RetrieveMemoryRecords` requests a second per account and Region", "`CreateEvent` takes a `clientToken`, so a retried write is ignored instead of stored twice", "Four built-in extraction strategies (semantic, user preference, summarisation, episodic), plus overrides and self-managed pipelines", "Unit prices are public, events expire on a set time to live of 7 to 365 days, and long-term records can take an optional time-to-live" ], "weaknesses": [ "Long-term extraction is asynchronous. The docs say records appear within seconds to minutes after a write", "No SLA names AgentCore. The Bedrock SLA of 4 October 2023 covers the Bedrock APIs for models", "Built-in strategies use cross-Region inference, so event text can be processed in another Region of the same geography", "Short-term memory billing moved from per event to per GB on 6 October 2026, with each event billed as at least 12 KB", "No Memory-specific CloudTrail page was found in the developer guide, and an AWS account needs a person to create it" ], "agentNotes": [ "Create the memory resource first and wait for it to become active (the guide says 2 to 3 minutes). Short-term events work without a strategy, long-term records need at least one", "Don't search for a fact straight after `CreateEvent`. Extraction runs in the background, so poll `ListMemoryRecords` or list extraction jobs before relying on `RetrieveMemoryRecords`", "Send `actorId`, `sessionId` and `eventTimestamp` on every `CreateEvent`, and reuse the same `clientToken` when retrying", "Pass `namespace` or `namespacePath` on every retrieval, and scope it to one actor so users' memories don't mix", "Treat retrieved records as untrusted input, and back off on 429 `ThrottledException` and 409 `RetryableConflictException`. A quota breach returns 402 `ServiceQuotaExceededException`" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 4, "avgRating": 3.5, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "A", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 79.7 } ], "editorialScores": { "ergonomics": 86, "maintenance": 83, "payments": 30, "reliability": 88, "schema": 92, "security": 87, "transparency": 64 }, "provenanceScore": 94, "checked": { "categories": { "ergonomics": "2026-11-01", "maintenance": "2026-11-01", "payments": "2026-11-01", "reliability": "2026-11-01", "schema": "2026-11-01", "security": "2026-11-01", "transparency": "2026-11-01" }, "last": "2026-11-01", "lastMoved": "2026-10-17", "oldest": "2026-11-01", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install bedrock-agentcore # AgentCore CLI: npm install -g @aws/agentcore", "http": "curl -X POST \"https://bedrock-agentcore.us-east-1.amazonaws.com/memories/$AGENTCORE_MEMORY_ID/retrieve\" \\\n --aws-sigv4 \"aws:amz:us-east-1:bedrock-agentcore\" --user \"$AWS_ACCESS_KEY_ID:$AWS_SECRET_ACCESS_KEY\" \\\n -H \"content-type: application/json\" \\\n -d '{\"namespace\":\"/users/alex/facts\",\"searchCriteria\":{\"searchQuery\":\"dietary preferences\",\"topK\":3}}'", "config": { "mcpServers": { "bedrock-agentcore-mcp-server": { "args": [ "awslabs.amazon-bedrock-agentcore-mcp-server@latest" ], "command": "uvx", "env": { "AGENTCORE_ENABLE_TOOLS": "memory", "FASTMCP_LOG_LEVEL": "ERROR" } } } } }, "letme": { "capability": "https://letme.dev/memory.store", "tool": "https://letme.dev/agentcore-memory" }, "sameCompany": [ "amazon-bedrock", "amazon-nova-embeddings", "amazon-bedrock-guardrails", "amazon-transcribe", "amazon-polly", "amazon-nova-sonic", "agentcore-identity", "aws-secrets-manager", "agentcore-web-search", "aws-mcp-servers", "amazon-ses", "amazon-location", "amazon-translate", "amazon-ads-api", "amazon-creators-api" ], "area": "agent-runtime", "unitPrices": [ { "item": "Short-term memory ingestion", "unit": "gb", "usd": 1, "note": "Per GB of event data ingested, each event billed as 12 KB to 64 KB. As of 6 October 2026" }, { "item": "Short-term memory retrieval", "unit": "gb", "usd": 0.2, "note": "Per GB of event data retrieved, same 12 KB minimum per event" }, { "item": "Short-term memory storage", "unit": "gb-month", "usd": 0.1, "note": "Prorated hourly over each event's time to live" }, { "item": "Long-term memory storage, built-in strategies", "unit": "record", "usd": 0.00075, "note": "$0.75 per 1,000 records a month" }, { "item": "Long-term memory storage, overrides or self-managed", "unit": "record", "usd": 0.00025, "note": "$0.25 per 1,000 records a month, model usage billed separately" }, { "item": "Long-term memory retrieval", "unit": "1k-requests", "usd": 0.5, "note": "Per 1,000 retrieve requests" } ], "provenance": { "legalEntity": "Amazon Web Services, Inc. (regional AWS entities by account location)", "domain": "amazon.com", "domainRegistered": "1994-11-01", "domainNote": "The service pages are under aws.amazon.com and the endpoints on amazonaws.com, an AWS domain. The registration date is the one on our other AWS listings and was not looked up again on 8 October 2026.", "endpointOnVendorDomain": true, "terms": "https://aws.amazon.com/service-terms/", "privacy": "https://aws.amazon.com/privacy/", "statusPage": "https://health.aws.amazon.com/health/status", "changelog": "https://docs.aws.amazon.com/bedrock-agentcore/latest/devguide/release-notes.html", "securityTxt": "valid", "checked": "2026-11-01", "notes": [ "The AWS Service Terms showed Last Updated 30 October 2026 on 1 November. Section 50 covers AWS AI services, and its only AgentCore-specific clause is 50.15 on AgentCore Payments. Section 50.3, which lets AWS use content from named AI services for improvement, does not list Bedrock or AgentCore.", "The AWS Privacy Notice showed Last Updated 18 May 2026 on 1 November.", "aws.amazon.com/.well-known/security.txt carries Expires 2027-10-16T16:25:03.000Z on 1 November 2026 (last modified 16 October), and points to the vulnerability disclosure programme on HackerOne and the policy at vdp.aws.security. A WebFetch read the same day returned an older copy with the September 2026 expiry, set aside because the direct read shows the live file.", "health.aws.amazon.com/health/status is drawn by script. The Bedrock AgentCore feeds for us-east-1 and us-west-2 had no items on 1 November 2026, and the dashboard's history file lists one event naming Bedrock AgentCore in the last 90 days, packet loss in one zone of eu-south-2 on 4 October 2026, a Region where Memory is not sold.", "The AWS SLA index does not name AgentCore. The only AgentCore SLA found is Sinnet's for the AWS China (Beijing) Region, last updated 30 September 2026." ], "score": 94 }, "requirements": { "setupChecked": true, "complianceChecked": true, "card": "unknown", "freeTier": true, "minutes": 15, "credential": "cloud-iam", "hosting": [ "US", "EU", "UK", "CA", "APAC" ], "euResidency": "yes", "trainsOnData": "unknown", "zeroRetention": "no", "certifications": [ "SOC 2 Type II", "ISO 27001", "ISO 27701", "HIPAA (BAA available)", "FedRAMP", "CSA STAR", "GDPR" ], "dpa": true, "selfHost": "no" }, "pageJsonUrl": "https://www.anchorterminal.com/tools/agentcore-memory.json", "live": { "slug": "agentcore-memory", "probe": { "target": "https://bedrock-agentcore.{region}.amazonaws.com", "method": "get", "lastAt": "2026-11-07T18:20:08.722484688Z", "lastOk": false, "lastStatus": 0, "lastMs": 0, "lastNote": "invalid character \"{\" in host name", "authRequired": false, "uptime24h": 0, "uptime30d": 0, "p50ms24h": 0, "p95ms24h": 0, "samples24h": 239, "samples30d": 7289, "days": [ { "date": "2026-10-09", "probes": 169, "ok": 0 }, { "date": "2026-10-10", "probes": 247, "ok": 0 }, { "date": "2026-10-11", "probes": 247, "ok": 0 }, { "date": "2026-10-12", "probes": 247, "ok": 0 }, { "date": "2026-10-13", "probes": 248, "ok": 0 }, { "date": "2026-10-14", "probes": 249, "ok": 0 }, { "date": "2026-10-15", "probes": 253, "ok": 0 }, { "date": "2026-10-16", "probes": 252, "ok": 0 }, { "date": "2026-10-17", "probes": 253, "ok": 0 }, { "date": "2026-10-18", "probes": 256, "ok": 0 }, { "date": "2026-10-19", "probes": 255, "ok": 0 }, { "date": "2026-10-20", "probes": 252, "ok": 0 }, { "date": "2026-10-21", "probes": 253, "ok": 0 }, { "date": "2026-10-22", "probes": 253, "ok": 0 }, { "date": "2026-10-23", "probes": 248, "ok": 0 }, { "date": "2026-10-24", "probes": 251, "ok": 0 }, { "date": "2026-10-25", "probes": 250, "ok": 0 }, { "date": "2026-10-26", "probes": 252, "ok": 0 }, { "date": "2026-10-27", "probes": 249, "ok": 0 }, { "date": "2026-10-28", "probes": 251, "ok": 0 }, { "date": "2026-10-29", "probes": 249, "ok": 0 }, { "date": "2026-10-30", "probes": 248, "ok": 0 }, { "date": "2026-10-31", "probes": 251, "ok": 0 }, { "date": "2026-11-01", "probes": 249, "ok": 0 }, { "date": "2026-11-02", "probes": 250, "ok": 0 }, { "date": "2026-11-03", "probes": 248, "ok": 0 }, { "date": "2026-11-04", "probes": 246, "ok": 0 }, { "date": "2026-11-05", "probes": 185, "ok": 0 }, { "date": "2026-11-06", "probes": 241, "ok": 0 }, { "date": "2026-11-07", "probes": 187, "ok": 0 } ], "outages": [ { "start": "2026-10-09T07:40:18.334133541Z", "end": "0001-01-01T00:00:00Z", "note": "invalid character \"{\" in host name" } ] }, "vendorStatus": { "page": "https://health.aws.amazon.com/health/status", "indicator": "unknown", "summary": "no machine-readable status found", "checkedAt": "2026-11-04T23:55:00.744654861Z" }, "versions": [ { "registry": "github", "name": "aws/bedrock-agentcore-sdk-python", "version": "v1.25.4", "released": "2026-11-06", "seenAt": "2026-11-06T23:03:36.17792927Z" }, { "registry": "npm", "name": "@aws-sdk/client-bedrock-agentcore", "version": "3.1164.0", "seenAt": "2026-11-06T23:03:33.952320496Z" }, { "registry": "npm", "name": "@aws/agentcore", "version": "1.0.2", "seenAt": "2026-11-06T23:03:34.181586614Z" }, { "registry": "pypi", "name": "awslabs.amazon-bedrock-agentcore-mcp-server", "version": "0.2.1", "released": "2026-09-08", "seenAt": "2026-11-06T23:03:36.168504989Z" }, { "registry": "pypi", "name": "bedrock-agentcore", "version": "1.25.4", "released": "2026-11-06", "seenAt": "2026-11-06T23:03:31.911712181Z" }, { "registry": "pypi", "name": "boto3", "version": "1.43.126", "released": "2026-11-06", "seenAt": "2026-11-06T23:03:32.061007831Z" } ], "githubStars": 783, "npmWeekly": 1446867, "pypiWeekly": 1658205, "securityTxt": { "url": "https://amazon.com/.well-known/security.txt", "state": "valid", "checkedAt": "2026-11-07T16:00:18.354437696Z" }, "llmsTxt": { "url": "https://docs.aws.amazon.com/bedrock-agentcore/latest/devguide/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:31:09.627847078Z" }, "domain": { "domain": "amazon.com", "registered": "1994-11-01", "source": "https://rdap.verisign.com/com/v1/domain/amazon.com", "checkedAt": "2026-11-01T14:09:08.477101866Z" }, "github": { "repo": "aws/bedrock-agentcore-sdk-python", "checkedAt": "2026-11-02T08:33:22.483521011Z", "stars": 782, "archived": false, "issuesEnabled": true, "pushedAt": "2026-10-30T13:45:55Z", "openIssues": 82, "openPRs": 51, "issuesOpened90d": 25, "issuesClosed90d": 13, "prsMerged90d": 46, "ci": { "branch": "main", "runs": 50, "success": 45, "failure": 5, "other": 0, "latest": "success", "latestAt": "2026-10-30T13:47:31Z" }, "advisories": [ { "ghsa": "GHSA-j6g5-3hh3-pgw8", "cve": "CVE-2026-16796", "severity": "high", "published": "2026-07-23T20:11:08Z" }, { "ghsa": "GHSA-hqf8-7w95-9r33", "cve": "CVE-2026-15737", "severity": "medium", "published": "2026-07-16T17:05:36Z" }, { "ghsa": "GHSA-6rfw-mq36-jm8h", "cve": "CVE-2026-12530", "severity": "high", "published": "2026-06-17T21:10:20Z" } ], "replies": { "sampled": 25, "unanswered": 13, "medianDays": 9.9 } }, "updatedAt": "2026-11-07T18:20:08.722484688Z" } }, "answer": "Amazon Bedrock AgentCore Memory scores 79.7 (A) on agent readiness against MemMachine's 58 (C), and leads in 5 of 7 scored categories. MemMachine leads on payments \u0026 pricing.", "b": { "slug": "memmachine", "name": "MemMachine", "vendor": "MemVerge, Inc.", "vendorUrl": "https://memmachine.ai", "kind": "http-api", "category": "agent-memory", "summary": "MemMachine is an open-source long-term memory layer for AI agents, incubated by MemVerge, with episodic, profile and working memory behind a self-hosted REST server, Python and TypeScript clients and an MCP server, plus a hosted platform.", "url": "https://www.anchorterminal.com/tools/memmachine", "markdownUrl": "https://www.anchorterminal.com/tools/memmachine.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/memmachine.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/memmachine.json", "dns": "memmachine.grade.anchorterminal.com", "repo": "https://github.com/MemMachine/MemMachine", "license": "Apache-2.0", "transports": [ "http", "stdio", "streamable-http" ], "packages": [ { "registry": "pypi", "name": "memmachine-server" }, { "registry": "pypi", "name": "memmachine-client" }, { "registry": "npm", "name": "@memmachine/client" } ], "auth": "none", "authNotes": "The self-hosted server takes no credential; the owner supplies LLM and embedding keys (OpenAI, Bedrock or Ollama) in its config. The hosted MemMachine Platform at api.memmachine.ai uses a bearer API key created and revoked in the console after a browser signup.", "pricing": "freemium", "pricingNotes": "Free under Apache-2.0 to self-host, with model costs paid to the chosen provider. The hosted platform has a free account per the README, but no prices were found, and the terms bill hosted services by order, monthly or annually.", "priceSummary": "Freemium", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the repository, the OpenAPI documents or the docs (checked 2026-11-06).", "endpoints": [] }, "toolCount": 3, "popularity": { "githubStars": 3085, "npmWeekly": 28, "pypiWeekly": 581, "asOf": "2026-11-06" }, "docsUrl": "https://docs.memmachine.ai", "llmsTxt": "https://docs.memmachine.ai/llms.txt", "openapi": "https://github.com/MemMachine/MemMachine/blob/main/docs/openapi.json", "capabilities": [ "memory.store", "memory.search", "memory.user", "memory.graph", "memory.delete" ], "tags": [ "open-source", "self-hosted", "hosted", "apache-2.0", "python", "typescript", "docker", "mcp", "openapi", "llms-txt", "no-auth", "pre-1.0" ], "lastRelease": "2026-10-08", "graded": true, "anchor": { "graded": true, "score": 58, "grade": "C", "agentReady": false, "rank": 767, "ranked": true, "rankOf": 1486, "categoryRank": 16, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 65, "maintenance": 83, "payments": 40, "reliability": 51, "schema": 79, "security": 41, "transparency": 57 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-06" }, "negative": 0, "verdict": "MemMachine is an Apache-2.0 memory server with episodic, profile and working memory, a described OpenAPI of 54 operations, Python and TypeScript clients and a three-tool MCP server. It is version 0.4.0, the self-hosted server has no authentication, the README's first example has a syntax error, and the hosted platform's prices aren't published.", "bestFor": "Self-hosted memory for agent frameworks that want episodic and profile memory with many integrations.", "strengths": [ "Apache-2.0 server and clients on PyPI, npm and Docker, self-hostable with Ollama or AWS Bedrock", "OpenAPI documents for the server (54 operations) and the hosted platform (12), every operation described", "MCP server over stdio or HTTP with three tools, add_memory, search_memory and delete_memory", "SECURITY.md with private reporting and a two-business-day acknowledgement, plus security-audit and SBOM workflows", "Hosted platform terms commit to 99.5% availability" ], "weaknesses": [ "Version 0.4.0 of 6 October 2026, pre-1.0, with no changelog file in the repository", "The self-hosted server has no authentication and no security scheme in its OpenAPI document", "The README's quick start imports with `from memmachine_client import import MemMachineClient`, which is invalid Python", "292 open issues and pull requests, including recent reports that a provider 429 becomes a 500 and that a 0.4.0 config no longer starts", "No prices for the hosted platform, and the Enterprise edition is marked coming soon" ], "agentNotes": [ "Import with `from memmachine_client import MemMachineClient`; the README line has a doubled `import`", "Keep the server on a private network or put an authenticating proxy in front, since it accepts any caller", "Scope every call with org, project, group, agent, user and session ids so memories don't mix", "Retry search after a short wait on 500s, which a recent issue ties to upstream provider rate limits", "Treat recalled episodes as untrusted text from past conversations" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "C", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 58 } ], "editorialScores": { "ergonomics": 65, "maintenance": 83, "payments": 40, "reliability": 51, "schema": 79, "security": 41, "transparency": 55 }, "provenanceScore": 58, "checked": { "categories": { "ergonomics": "2026-11-06", "maintenance": "2026-11-06", "payments": "2026-11-06", "reliability": "2026-11-06", "schema": "2026-11-06", "security": "2026-11-06", "transparency": "2026-11-06" }, "last": "2026-11-06", "oldest": "2026-11-06", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install memmachine-server memmachine-client", "http": "curl http://localhost:8080/api/v2/health" }, "letme": { "capability": "https://letme.dev/memory.store", "tool": "https://letme.dev/memmachine" }, "area": "agent-runtime", "provenance": { "legalEntity": "MemVerge, Inc.", "domain": "memmachine.ai", "domainRegistered": "2025-08-15", "endpointOnVendorDomain": null, "terms": "https://memmachine.ai/terms-of-service/", "privacy": "https://memmachine.ai/privacy-policy/", "statusPage": "", "changelog": "https://github.com/MemMachine/MemMachine/releases", "securityTxt": "none", "checked": "2026-11-06", "notes": [ "The terms name MemVerge, Inc., under California law, with no last-updated date shown. They forbid web scraping or harvesting data from the services, recorded here as a fact. The open-source software is Apache-2.0 and outside the terms.", "memmachine.ai/robots.txt allows all crawlers. docs.memmachine.ai carries Content-Signal ai-input=yes.", "RDAP gives memmachine.ai a registration date of 15 August 2025.", "/.well-known/security.txt returns 404. No status page found." ], "score": 58 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/memmachine.json", "live": { "slug": "memmachine", "versions": [ { "registry": "github", "name": "MemMachine/MemMachine", "version": "v0.4.0", "released": "2026-10-08", "seenAt": "2026-11-06T23:43:57.45502049Z" }, { "registry": "npm", "name": "@memmachine/client", "version": "0.3.9", "seenAt": "2026-11-06T23:43:56.945798416Z" }, { "registry": "pypi", "name": "memmachine-client", "version": "0.4.0", "released": "2026-10-08", "seenAt": "2026-11-06T23:43:55.050118334Z" }, { "registry": "pypi", "name": "memmachine-server", "version": "0.4.0", "released": "2026-10-08", "seenAt": "2026-11-06T23:43:54.864236924Z" } ], "githubStars": 3085, "npmWeekly": 28, "pypiWeekly": 54, "securityTxt": { "url": "https://memmachine.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-07T16:00:09.818703565Z" }, "llmsTxt": { "url": "https://docs.memmachine.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:32:59.84146138Z" }, "pages": [ { "url": "https://memmachine.ai/privacy-policy/", "kind": "privacy", "status": 200, "checkedAt": "2026-11-07T14:14:11.012100581Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "19edc6281451" }, { "url": "https://memmachine.ai/terms-of-service/", "kind": "terms", "status": 200, "checkedAt": "2026-11-07T14:14:13.19202427Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "079364130152" } ], "updatedAt": "2026-11-07T16:00:09.818703565Z" } }, "edges": [ { "by": 46, "category": "security", "leads": "agentcore-memory", "name": "Security \u0026 auth", "reasons": { "a": "IAM with SigV4, roles and short-lived credentials, resource-based policies on the memory resource, and OAuth (JWT) for end users through an AgentCore Gateway (30). Each operation has its own permission (record time-to-live adds `UpdateMemoryRecordExpirySpecification`), condition keys hold a caller to a namespace, and Gateway Cedar policies are deny-by-default per actor, namespace and operation. The three batch operations are outside those policies, and deletes are permanent with no confirmation step (17 of 20). The guide names memory poisoning and prompt injection, places prevention with the customer, and recommends Bedrock Guardrails on input before `CreateEvent` and adversarial testing. The MCP server README says retrieved records are untrusted input (12 of 15). CloudWatch metrics and optional vended logs for extraction. The data protection page recommends CloudTrail in general terms, and we found no Memory-specific CloudTrail page such as Gateway and Registry have (10 of 15). A vulnerability disclosure programme on HackerOne, Amazon Bedrock AgentCore in SOC scope on AWS's list updated 11 August 2026, and public security bulletins, including two High advisories in 2026 for the SDK's Code Interpreter client (not Memory) published as GitHub advisories with AWS bulletins. aws.amazon.com/.well-known/security.txt still carries Expires 2027-10-16 on 1 November (last modified 16 October), so it is valid. The disclosure policy at vdp.aws.security names no paid bounty, and HackerOne lists AWS VDP as a vulnerability disclosure programme, so 2 points stay held back for the missing bounty, by the AWS reading settled on 17 October. (18 of 20). 30+17+12+10+18 = 87.", "b": "Framework reading for software the owner runs. The server has no authentication and no security scheme in its OpenAPI document (15 of 30). No read-only mode or confirmation for deletes (5 of 20). No guidance on recalled memories as untrusted text (4 of 15). No audit log on the self-hosted server; the hosted console shows usage (5 of 15). SECURITY.md with GitHub private reporting and a two-business-day acknowledgement, with security-audit and SBOM workflows; no security.txt or certification (12 of 20). Total 41." }, "scores": { "a": 87, "b": 41 } }, { "by": 37, "category": "reliability", "leads": "agentcore-memory", "name": "Reliability", "reasons": { "a": "Graded as a hosted API, the AWS data plane that agents call. AWS Health Dashboard with per-service, per-Region history and RSS feeds (20). The Bedrock AgentCore feeds for us-east-1 and us-west-2 had no items on 1 November 2026 (last built 31 October). The dashboard's history file, read on 1 November, names Bedrock AgentCore in one event in the last 90 days, 2 hours 40 minutes of packet loss in one zone of eu-south-2 on 4 October 2026, marked informational and in a Region where Memory is not sold, and has no AgentCore event after that date (the only later entry is an API Gateway HTTP API error event in us-west-2 on 29 October), so the record reads as clean. The public dashboard lists only broad events (30). Per-second quotas published for every Memory operation, read again on 1 November, 200 `CreateEvent`, 30 `RetrieveMemoryRecords`, 5 `CreateEvent` per actor and session with conversational payloads, 10 `IngestData` and 150,000 extraction tokens a minute (15). 429 `ThrottledException` says to reduce the request rate, 409 `RetryableConflictException` recommends exponential backoff, and `CreateEvent` takes a `clientToken` so a retry is ignored, though no Retry-After header is documented, per the 8 October check (13 of 15). No SLA found for Memory. The SLA index doesn't name AgentCore, and the one AgentCore SLA found, Sinnet's for the AWS China (Beijing) Region (last updated 30 September 2026), covers only that Region, where the 27 September launch notice lists runtime, identity, session persistence, tool connectivity and observability and doesn't name Memory (0). Generally available since October 2025 per the release notes (10).", "b": "Local-software lines, as a server the owner runs. `memmachine-server` and `memmachine-client` on PyPI with Python versions stated, a Docker image and a compose script (20). pytest, integration and installation-test workflows exist, but GitHub's API answered with a rate limit, so run results were unread (15 of 25, unchecked). 292 open issues and pull requests; the newest bug reports, including a 429 from a provider surfacing as a 500 and a 0.4.0 configuration that no longer starts, have zero to two replies (10 of 25). No changelog file, release notes only on GitHub, which weren't read, and pre-1.0 tags (6 of 15). Version 0.4.0 (0). Total 51." }, "scores": { "a": 88, "b": 51 } }, { "by": 22, "category": "transparency", "leads": "agentcore-memory", "name": "Transparency \u0026 trust", "reasons": { "a": "Closed service under the AWS Customer Agreement and Service Terms (updated 30 October 2026), with the Python SDK and CLI under Apache-2.0 (18 of 30, as for S3). Section 50.3 of the Service Terms does not list Bedrock or AgentCore among the services whose content AWS may use for improvement, events expire after 7 to 365 days, long-term records can carry an optional time-to-live since October 2026 (by default they do not expire), records are encrypted at rest with KMS, and the terms carry the AWS DPA. The AgentCore data protection page has Gateway-specific statements and none for Memory, and no retention period for deleted records was found (22 of 30). The pricing page dates the short-term pricing change (through 5 October, as of 6 October 2026), but no deprecation policy for the Memory API was found (6 of 20). A sub-processor page updated 30 October 2026 and a per-Region availability table. Built-in strategies may process event text in another Region of the same geography, which the cross-Region inference page states (18 of 20).", "b": "Apache-2.0 (30). The terms say hosted customer data is destroyed on termination, with no period, and use usage data only in aggregate; the privacy policy wasn't read (12 of 30). No deprecation policy or notices found (3 of 20). No telemetry calls found in the server or client source, and the docs don't address it (10 of 20). Total 55." }, "scores": { "a": 79, "b": 57 } }, { "by": 21, "category": "ergonomics", "leads": "agentcore-memory", "name": "Agent ergonomics", "reasons": { "a": "Graded on the API. `RetrieveMemoryRecords` returns record summaries with a relevance score, sized by `topK` (default 10, maximum 100) and `maxResults` (default 20), and long-term records stand in for full history, but no field selection was found (20 of 25). `nextToken` pagination, namespace and namespace path scoping, a strategy filter and metadata filters (20). Typed exceptions with HTTP codes and advice in each description. A quota breach returns 402 `ServiceQuotaExceededException` beside the 429 `ThrottledException`, which a generic client may misread (18 of 20). `clientToken` on `CreateEvent`, immutable events and side-effect-free reads. We did not confirm a token on `IngestData` or the batch operations (18 of 20). SDKs in Python, JavaScript, Java, Go and five other languages plus a higher-level Python SDK, but a memory resource must exist first (2 to 3 minutes to create), `eventTimestamp` is required and every call needs SigV4 signing (10 of 15). The awslabs MCP server's 21 Memory tools sit among 122, and one environment variable registers Memory alone.", "b": "Searches take limit and filter options for episodic and semantic results (20 of 25). Memories can be listed and filtered by scope (15 of 20). Validation errors are typed; other failures are less clear, as the 429-to-500 issue shows (10 of 20). No idempotency keys or safe-retry guidance found (5 of 20). Python and TypeScript clients and a five-line quick start, once the import is fixed (15). Total 65." }, "scores": { "a": 86, "b": 65 } }, { "by": 13, "category": "schema", "leads": "agentcore-memory", "name": "Schema \u0026 documentation", "reasons": { "a": "The SDKs are generated from AWS's published service models, and the API reference gives every field with type, length, pattern and valid values (25). The developer guide has an llms.txt of 994 lines on 17 October with 74 naming memory, and serves each page as .md (10). The guides say when to use `IngestData` instead of `CreateEvent`, which payload types are extracted, and how long-term memory differs from retrieval-augmented generation, but give little on when the service is the wrong tool (16 of 20). Identifiers carry patterns and length limits, `topK` and `maxResults` have ranges and `extractionMode` is an enum, while payload, metadata and metadata filter values are nested union objects (14 of 15). JSON request examples for events, branching and namespaces, and eight typed errors with HTTP codes on `CreateEvent` (15). Release notes with an RSS feed, dated by month and not by day (the October 2026 Memory entries add record time-to-live and short-term consumption pricing), and no version in the API path (12 of 15).", "b": "OpenAPI documents for the server (54 operations) and the hosted platform (12) (25). llms.txt on docs.memmachine.ai with Markdown pages (10). Every operation has a description, and the docs explain memory types and scoping (15 of 20). Typed request models generated from the server, with search options for limits and filters (12 of 15). Examples for each client and the MCP tools, but only 422 is documented on the server and the README's first example doesn't run (8 of 15). `/api/v2` paths and tagged releases, no changelog (9 of 15). Total 79." }, "scores": { "a": 92, "b": 79 } }, { "by": 10, "category": "payments", "leads": "memmachine", "name": "Payments \u0026 pricing", "reasons": { "a": "No x402, MPP or L402 on the Memory endpoints (0). Per-GB, per-record and per-retrieval prices published without a login, with a worked example (20). No Memory-specific free tier or sandbox. New AWS accounts get up to $200 in Free Tier credits, and the Free Tier FAQ says most new customers don't need a payment method while AWS may still ask for one, so half, as on our other AWS listings (10). A person creates the AWS account and sets up IAM (0).", "b": "Self-hosted rule, with the price lines read for the hosted platform. No x402, MPP or L402 (0 of 40). No hosted prices found on the site or docs (0). Free to self-host with no card (20). An agent can install it from PyPI with no account (20). Total 40." }, "scores": { "a": 30, "b": 40 } } ], "facts": [ { "a": "HTTP API", "b": "HTTP API", "name": "Kind" }, { "a": "Amazon Web Services", "b": "MemVerge, Inc.", "name": "Vendor" }, { "a": "https://bedrock-agentcore.{region}.amazonaws.com", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "HTTP, stdio", "b": "HTTP, stdio, Streamable HTTP", "name": "Transports" }, { "a": "OAuth or key", "b": "None", "name": "Auth" }, { "a": "Pay per use", "b": "Freemium", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Proprietary service under the AWS Customer Agreement and Service Terms. The `bedrock-agentcore` Python SDK and the `@aws/agentcore` CLI are Apache-2.0", "b": "Apache-2.0", "name": "Licence" }, { "a": "21", "b": "3", "name": "Tools exposed" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-30", "b": "2026-10-08", "name": "Last release" }, { "a": "2026-10-01", "b": "no date given", "name": "Terms last updated" }, { "a": "2026-05-18", "b": "2026-05-20", "name": "Privacy policy last updated" }, { "a": "yes, with an opt-out", "b": "not found in the text", "name": "Customer content may train models" }, { "a": "yes", "b": "yes", "name": "Terms restrict automated access" }, { "a": "yes", "b": "yes", "name": "Terms restrict benchmarking" }, { "a": "yes", "b": "not found in the text", "name": "Terms or service can change without notice" }, { "a": "not found in the text", "b": "yes", "name": "Arbitration or class-action waiver" }, { "a": "776 stars, 1.1M npm/wk", "b": "3.1k stars, 28 npm/wk, 581 PyPI/wk", "name": "Popularity" }, { "a": "3.5/5 (4)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "Amazon Bedrock AgentCore Memory scores 79.7 (A) on agent readiness against MemMachine's 58 (C), and leads in 5 of 7 scored categories. MemMachine leads on payments \u0026 pricing.", "question": "Which is better for AI agents, Amazon Bedrock AgentCore Memory or MemMachine?" }, { "answer": "Amazon Bedrock AgentCore Memory takes an API key or an OAuth sign-in. MemMachine needs no key.", "question": "Do Amazon Bedrock AgentCore Memory and MemMachine need an API key?" }, { "answer": "Amazon Bedrock AgentCore Memory has a hosted endpoint at https://bedrock-agentcore.{region}.amazonaws.com. MemMachine runs on your own machine, with no hosted endpoint listed.", "question": "Can an agent call Amazon Bedrock AgentCore Memory and MemMachine without installing anything?" }, { "answer": "No open-source release is listed for Amazon Bedrock AgentCore Memory. MemMachine is open source (Apache-2.0).", "question": "Are Amazon Bedrock AgentCore Memory and MemMachine open source?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 88 against 51", "Schema \u0026 documentation, 92 against 79", "Agent ergonomics, 86 against 65", "Security \u0026 auth, 87 against 41", "Transparency \u0026 trust, 79 against 57" ], "also": [ "Agent-ready, a grade of BB or better", "A hosted endpoint, with nothing to install" ], "goodFor": "Teams already on AWS that want per-user memory under IAM, KMS and Regional controls, with extraction run for them.", "slug": "agentcore-memory", "watchFor": "Long-term extraction is asynchronous. The docs say records appear within seconds to minutes after a write" }, { "aheadOn": [ "Payments \u0026 pricing, 40 against 30" ], "also": [ "No key needed to call it", "Open source" ], "goodFor": "Self-hosted memory for agent frameworks that want episodic and profile memory with many integrations.", "slug": "memmachine", "watchFor": "Version 0.4.0 of 6 October 2026, pre-1.0, with no changelog file in the repository" } ], "history": { "agentcore-memory": [ { "causes": [ "security" ], "date": "2026-10-17", "delta": 0.3, "from": 79.4, "fromGrade": "A", "to": 79.7, "toGrade": "A" } ], "memmachine": null }, "job": { "capability": "memory.store", "name": "Agent memory" }, "others": [ { "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-basic-memory.json", "title": "Amazon Bedrock AgentCore Memory vs Basic Memory", "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-basic-memory" }, { "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-claude-mem.json", "title": "Amazon Bedrock AgentCore Memory vs claude-mem", "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-claude-mem" }, { "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-cognee.json", "title": "Amazon Bedrock AgentCore Memory vs Cognee", "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-cognee" }, { "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-everos.json", "title": "Amazon Bedrock AgentCore Memory vs EverOS", "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-everos" }, { "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-google-memory-bank.json", "title": "Amazon Bedrock AgentCore Memory vs Agent Platform Memory Bank", "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-google-memory-bank" }, { "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-graphicle.json", "title": "Amazon Bedrock AgentCore Memory vs Graphicle", "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-graphicle" }, { "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-graphiti.json", "title": "Amazon Bedrock AgentCore Memory vs Graphiti", "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-graphiti" }, { "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-hindsight.json", "title": "Amazon Bedrock AgentCore Memory vs Hindsight", "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-hindsight" }, { "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-honcho.json", "title": "Amazon Bedrock AgentCore Memory vs Honcho", "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-honcho" }, { "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-hy-memory.json", "title": "Amazon Bedrock AgentCore Memory vs Hy Memory", "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-hy-memory" }, { "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-langmem.json", "title": "Amazon Bedrock AgentCore Memory vs LangMem", "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-langmem" }, { "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-localghost.json", "title": "Amazon Bedrock AgentCore Memory vs LocalGhost", "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-localghost" }, { "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-mem0.json", "title": "Amazon Bedrock AgentCore Memory vs Mem0 Platform + MCP", "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-mem0" }, { "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-memori.json", "title": "Amazon Bedrock AgentCore Memory vs Memori", "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-memori" }, { "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-memory-reference-server.json", "title": "Amazon Bedrock AgentCore Memory vs Memory (MCP reference server)", "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-memory-reference-server" }, { "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-mempalace.json", "title": "Amazon Bedrock AgentCore Memory vs MemPalace", "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-mempalace" }, { "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-past-dev.json", "title": "Amazon Bedrock AgentCore Memory vs past.dev", "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-past-dev" }, { "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-supermemory.json", "title": "Amazon Bedrock AgentCore Memory vs Supermemory API + MCP", "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-supermemory" }, { "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-tencentdb-agent-memory.json", "title": "Amazon Bedrock AgentCore Memory vs TencentDB Agent Memory", "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-tencentdb-agent-memory" }, { "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-tokenrip.json", "title": "Amazon Bedrock AgentCore Memory vs Tokenrip", "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-tokenrip" }, { "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-zep.json", "title": "Amazon Bedrock AgentCore Memory vs Zep", "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-zep" }, { "json": "https://www.anchorterminal.com/compare/basic-memory-vs-memmachine.json", "title": "Basic Memory vs MemMachine", "url": "https://www.anchorterminal.com/compare/basic-memory-vs-memmachine" }, { "json": "https://www.anchorterminal.com/compare/claude-mem-vs-memmachine.json", "title": "claude-mem vs MemMachine", "url": "https://www.anchorterminal.com/compare/claude-mem-vs-memmachine" }, { "json": "https://www.anchorterminal.com/compare/cognee-vs-memmachine.json", "title": "Cognee vs MemMachine", "url": "https://www.anchorterminal.com/compare/cognee-vs-memmachine" }, { "json": "https://www.anchorterminal.com/compare/everos-vs-memmachine.json", "title": "EverOS vs MemMachine", "url": "https://www.anchorterminal.com/compare/everos-vs-memmachine" }, { "json": "https://www.anchorterminal.com/compare/google-memory-bank-vs-memmachine.json", "title": "Agent Platform Memory Bank vs MemMachine", "url": "https://www.anchorterminal.com/compare/google-memory-bank-vs-memmachine" }, { "json": "https://www.anchorterminal.com/compare/graphiti-vs-memmachine.json", "title": "Graphiti vs MemMachine", "url": "https://www.anchorterminal.com/compare/graphiti-vs-memmachine" }, { "json": "https://www.anchorterminal.com/compare/hindsight-vs-memmachine.json", "title": "Hindsight vs MemMachine", "url": "https://www.anchorterminal.com/compare/hindsight-vs-memmachine" }, { "json": "https://www.anchorterminal.com/compare/honcho-vs-memmachine.json", "title": "Honcho vs MemMachine", "url": "https://www.anchorterminal.com/compare/honcho-vs-memmachine" }, { "json": "https://www.anchorterminal.com/compare/hy-memory-vs-memmachine.json", "title": "Hy Memory vs MemMachine", "url": "https://www.anchorterminal.com/compare/hy-memory-vs-memmachine" }, { "json": "https://www.anchorterminal.com/compare/langmem-vs-memmachine.json", "title": "LangMem vs MemMachine", "url": "https://www.anchorterminal.com/compare/langmem-vs-memmachine" }, { "json": "https://www.anchorterminal.com/compare/localghost-vs-memmachine.json", "title": "LocalGhost vs MemMachine", "url": "https://www.anchorterminal.com/compare/localghost-vs-memmachine" }, { "json": "https://www.anchorterminal.com/compare/mem0-vs-memmachine.json", "title": "Mem0 Platform + MCP vs MemMachine", "url": "https://www.anchorterminal.com/compare/mem0-vs-memmachine" }, { "json": "https://www.anchorterminal.com/compare/memmachine-vs-memori.json", "title": "MemMachine vs Memori", "url": "https://www.anchorterminal.com/compare/memmachine-vs-memori" }, { "json": "https://www.anchorterminal.com/compare/memmachine-vs-memory-reference-server.json", "title": "MemMachine vs Memory (MCP reference server)", "url": "https://www.anchorterminal.com/compare/memmachine-vs-memory-reference-server" }, { "json": "https://www.anchorterminal.com/compare/memmachine-vs-mempalace.json", "title": "MemMachine vs MemPalace", "url": "https://www.anchorterminal.com/compare/memmachine-vs-mempalace" }, { "json": "https://www.anchorterminal.com/compare/memmachine-vs-past-dev.json", "title": "MemMachine vs past.dev", "url": "https://www.anchorterminal.com/compare/memmachine-vs-past-dev" }, { "json": "https://www.anchorterminal.com/compare/memmachine-vs-supermemory.json", "title": "MemMachine vs Supermemory API + MCP", "url": "https://www.anchorterminal.com/compare/memmachine-vs-supermemory" }, { "json": "https://www.anchorterminal.com/compare/memmachine-vs-tencentdb-agent-memory.json", "title": "MemMachine vs TencentDB Agent Memory", "url": "https://www.anchorterminal.com/compare/memmachine-vs-tencentdb-agent-memory" }, { "json": "https://www.anchorterminal.com/compare/memmachine-vs-tokenrip.json", "title": "MemMachine vs Tokenrip", "url": "https://www.anchorterminal.com/compare/memmachine-vs-tokenrip" }, { "json": "https://www.anchorterminal.com/compare/memmachine-vs-zep.json", "title": "MemMachine vs Zep", "url": "https://www.anchorterminal.com/compare/memmachine-vs-zep" }, { "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-ai-memory.json", "title": "Amazon Bedrock AgentCore Memory vs AI Memory", "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-ai-memory" }, { "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-context-mode.json", "title": "Amazon Bedrock AgentCore Memory vs Context Mode Engine", "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-context-mode" }, { "json": "https://www.anchorterminal.com/compare/ai-memory-vs-memmachine.json", "title": "AI Memory vs MemMachine", "url": "https://www.anchorterminal.com/compare/ai-memory-vs-memmachine" }, { "json": "https://www.anchorterminal.com/compare/context-mode-vs-memmachine.json", "title": "Context Mode Engine vs MemMachine", "url": "https://www.anchorterminal.com/compare/context-mode-vs-memmachine" }, { "json": "https://www.anchorterminal.com/compare/graphicle-vs-memmachine.json", "title": "Graphicle vs MemMachine", "url": "https://www.anchorterminal.com/compare/graphicle-vs-memmachine" } ], "panel": null, "scores": [ { "agentcore-memory": 88, "by": 37, "edge": "agentcore-memory", "key": "reliability", "memmachine": 51, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "agentcore-memory": 92, "by": 13, "edge": "agentcore-memory", "key": "schema", "memmachine": 79, "name": "Schema \u0026 documentation", "weight": 13 }, { "agentcore-memory": 86, "by": 21, "edge": "agentcore-memory", "key": "ergonomics", "memmachine": 65, "name": "Agent ergonomics", "weight": 13 }, { "agentcore-memory": 87, "by": 46, "edge": "agentcore-memory", "key": "security", "memmachine": 41, "name": "Security \u0026 auth", "weight": 14 }, { "agentcore-memory": 30, "by": 10, "edge": "memmachine", "key": "payments", "memmachine": 40, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "agentcore-memory": 83, "by": 0, "edge": "", "key": "maintenance", "memmachine": 83, "name": "Maintenance \u0026 community", "weight": 7 }, { "agentcore-memory": 79, "by": 22, "edge": "agentcore-memory", "key": "transparency", "memmachine": 57, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Amazon Bedrock AgentCore Memory scores 79.7 (A) on agent readiness against MemMachine's 58 (C), and leads in 5 of 7 scored categories. MemMachine leads on payments \u0026 pricing. Both do agent memory.", "tasks": null, "tutorials": [], "verdicts": { "agentcore-memory": "Access is IAM-controlled down to one namespace, with published per-second quotas for every operation and a `clientToken` on event writes. Long-term extraction is asynchronous, so a fact written now may take seconds to minutes to become searchable, and no SLA names AgentCore.", "memmachine": "MemMachine is an Apache-2.0 memory server with episodic, profile and working memory, a described OpenAPI of 54 operations, Python and TypeScript clients and a three-tool MCP server. It is version 0.4.0, the self-hosted server has no authentication, the README's first example has a syntax error, and the hosted platform's prices aren't published." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/agentcore-memory-vs-memmachine", "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-memmachine.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/agentcore-memory-vs-memmachine.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/agentcore-memory-vs-memmachine.min.md" }, "markdown": "Amazon Bedrock AgentCore Memory scores 79.7 (A) on agent readiness against MemMachine's 58 (C), and leads in 5 of 7 scored categories. MemMachine leads on payments \u0026 pricing. Both do agent memory.\n\n- Amazon Bedrock AgentCore Memory: grade A, 79.7/100, rank #17 of 1486. Markdown https://www.anchorterminal.com/tools/agentcore-memory.md · JSON https://www.anchorterminal.com/api/v1/tools/agentcore-memory.json\n- MemMachine: grade C, 58/100, rank #767 of 1486. Markdown https://www.anchorterminal.com/tools/memmachine.md · JSON https://www.anchorterminal.com/api/v1/tools/memmachine.json\n- Best memory layers for AI agents: https://www.anchorterminal.com/best/agent-memory/index.md\n- All 353 memory comparisons: https://www.anchorterminal.com/compare/agent-memory/index.md\n\n## Which one, for what\n\n### Amazon Bedrock AgentCore Memory (A)\n\nGood for: Teams already on AWS that want per-user memory under IAM, KMS and Regional controls, with extraction run for them.\n\nAhead on:\n- Reliability, 88 against 51\n- Schema \u0026 documentation, 92 against 79\n- Agent ergonomics, 86 against 65\n- Security \u0026 auth, 87 against 41\n- Transparency \u0026 trust, 79 against 57\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n- A hosted endpoint, with nothing to install\n\nWatch for: Long-term extraction is asynchronous. The docs say records appear within seconds to minutes after a write\n\n### MemMachine (C)\n\nGood for: Self-hosted memory for agent frameworks that want episodic and profile memory with many integrations.\n\nAhead on:\n- Payments \u0026 pricing, 40 against 30\n\nAlso in its favour:\n- No key needed to call it\n- Open source\n\nWatch for: Version 0.4.0 of 6 October 2026, pre-1.0, with no changelog file in the repository\n\n\n## Why the edge\n\n### Security \u0026 auth: Amazon Bedrock AgentCore Memory +46\n\n- Amazon Bedrock AgentCore Memory (87): IAM with SigV4, roles and short-lived credentials, resource-based policies on the memory resource, and OAuth (JWT) for end users through an AgentCore Gateway (30). Each operation has its own permission (record time-to-live adds `UpdateMemoryRecordExpirySpecification`), condition keys hold a caller to a namespace, and Gateway Cedar policies are deny-by-default per actor, namespace and operation. The three batch operations are outside those policies, and deletes are permanent with no confirmation step (17 of 20). The guide names memory poisoning and prompt injection, places prevention with the customer, and recommends Bedrock Guardrails on input before `CreateEvent` and adversarial testing. The MCP server README says retrieved records are untrusted input (12 of 15). CloudWatch metrics and optional vended logs for extraction. The data protection page recommends CloudTrail in general terms, and we found no Memory-specific CloudTrail page such as Gateway and Registry have (10 of 15). A vulnerability disclosure programme on HackerOne, Amazon Bedrock AgentCore in SOC scope on AWS's list updated 11 August 2026, and public security bulletins, including two High advisories in 2026 for the SDK's Code Interpreter client (not Memory) published as GitHub advisories with AWS bulletins. aws.amazon.com/.well-known/security.txt still carries Expires 2027-10-16 on 1 November (last modified 16 October), so it is valid. The disclosure policy at vdp.aws.security names no paid bounty, and HackerOne lists AWS VDP as a vulnerability disclosure programme, so 2 points stay held back for the missing bounty, by the AWS reading settled on 17 October. (18 of 20). 30+17+12+10+18 = 87.\n- MemMachine (41): Framework reading for software the owner runs. The server has no authentication and no security scheme in its OpenAPI document (15 of 30). No read-only mode or confirmation for deletes (5 of 20). No guidance on recalled memories as untrusted text (4 of 15). No audit log on the self-hosted server; the hosted console shows usage (5 of 15). SECURITY.md with GitHub private reporting and a two-business-day acknowledgement, with security-audit and SBOM workflows; no security.txt or certification (12 of 20). Total 41.\n\n### Reliability: Amazon Bedrock AgentCore Memory +37\n\n- Amazon Bedrock AgentCore Memory (88): Graded as a hosted API, the AWS data plane that agents call. AWS Health Dashboard with per-service, per-Region history and RSS feeds (20). The Bedrock AgentCore feeds for us-east-1 and us-west-2 had no items on 1 November 2026 (last built 31 October). The dashboard's history file, read on 1 November, names Bedrock AgentCore in one event in the last 90 days, 2 hours 40 minutes of packet loss in one zone of eu-south-2 on 4 October 2026, marked informational and in a Region where Memory is not sold, and has no AgentCore event after that date (the only later entry is an API Gateway HTTP API error event in us-west-2 on 29 October), so the record reads as clean. The public dashboard lists only broad events (30). Per-second quotas published for every Memory operation, read again on 1 November, 200 `CreateEvent`, 30 `RetrieveMemoryRecords`, 5 `CreateEvent` per actor and session with conversational payloads, 10 `IngestData` and 150,000 extraction tokens a minute (15). 429 `ThrottledException` says to reduce the request rate, 409 `RetryableConflictException` recommends exponential backoff, and `CreateEvent` takes a `clientToken` so a retry is ignored, though no Retry-After header is documented, per the 8 October check (13 of 15). No SLA found for Memory. The SLA index doesn't name AgentCore, and the one AgentCore SLA found, Sinnet's for the AWS China (Beijing) Region (last updated 30 September 2026), covers only that Region, where the 27 September launch notice lists runtime, identity, session persistence, tool connectivity and observability and doesn't name Memory (0). Generally available since October 2025 per the release notes (10).\n- MemMachine (51): Local-software lines, as a server the owner runs. `memmachine-server` and `memmachine-client` on PyPI with Python versions stated, a Docker image and a compose script (20). pytest, integration and installation-test workflows exist, but GitHub's API answered with a rate limit, so run results were unread (15 of 25, unchecked). 292 open issues and pull requests; the newest bug reports, including a 429 from a provider surfacing as a 500 and a 0.4.0 configuration that no longer starts, have zero to two replies (10 of 25). No changelog file, release notes only on GitHub, which weren't read, and pre-1.0 tags (6 of 15). Version 0.4.0 (0). Total 51.\n\n### Transparency \u0026 trust: Amazon Bedrock AgentCore Memory +22\n\n- Amazon Bedrock AgentCore Memory (79): Closed service under the AWS Customer Agreement and Service Terms (updated 30 October 2026), with the Python SDK and CLI under Apache-2.0 (18 of 30, as for S3). Section 50.3 of the Service Terms does not list Bedrock or AgentCore among the services whose content AWS may use for improvement, events expire after 7 to 365 days, long-term records can carry an optional time-to-live since October 2026 (by default they do not expire), records are encrypted at rest with KMS, and the terms carry the AWS DPA. The AgentCore data protection page has Gateway-specific statements and none for Memory, and no retention period for deleted records was found (22 of 30). The pricing page dates the short-term pricing change (through 5 October, as of 6 October 2026), but no deprecation policy for the Memory API was found (6 of 20). A sub-processor page updated 30 October 2026 and a per-Region availability table. Built-in strategies may process event text in another Region of the same geography, which the cross-Region inference page states (18 of 20).\n- MemMachine (57): Apache-2.0 (30). The terms say hosted customer data is destroyed on termination, with no period, and use usage data only in aggregate; the privacy policy wasn't read (12 of 30). No deprecation policy or notices found (3 of 20). No telemetry calls found in the server or client source, and the docs don't address it (10 of 20). Total 55.\n\n### Agent ergonomics: Amazon Bedrock AgentCore Memory +21\n\n- Amazon Bedrock AgentCore Memory (86): Graded on the API. `RetrieveMemoryRecords` returns record summaries with a relevance score, sized by `topK` (default 10, maximum 100) and `maxResults` (default 20), and long-term records stand in for full history, but no field selection was found (20 of 25). `nextToken` pagination, namespace and namespace path scoping, a strategy filter and metadata filters (20). Typed exceptions with HTTP codes and advice in each description. A quota breach returns 402 `ServiceQuotaExceededException` beside the 429 `ThrottledException`, which a generic client may misread (18 of 20). `clientToken` on `CreateEvent`, immutable events and side-effect-free reads. We did not confirm a token on `IngestData` or the batch operations (18 of 20). SDKs in Python, JavaScript, Java, Go and five other languages plus a higher-level Python SDK, but a memory resource must exist first (2 to 3 minutes to create), `eventTimestamp` is required and every call needs SigV4 signing (10 of 15). The awslabs MCP server's 21 Memory tools sit among 122, and one environment variable registers Memory alone.\n- MemMachine (65): Searches take limit and filter options for episodic and semantic results (20 of 25). Memories can be listed and filtered by scope (15 of 20). Validation errors are typed; other failures are less clear, as the 429-to-500 issue shows (10 of 20). No idempotency keys or safe-retry guidance found (5 of 20). Python and TypeScript clients and a five-line quick start, once the import is fixed (15). Total 65.\n\n### Schema \u0026 documentation: Amazon Bedrock AgentCore Memory +13\n\n- Amazon Bedrock AgentCore Memory (92): The SDKs are generated from AWS's published service models, and the API reference gives every field with type, length, pattern and valid values (25). The developer guide has an llms.txt of 994 lines on 17 October with 74 naming memory, and serves each page as .md (10). The guides say when to use `IngestData` instead of `CreateEvent`, which payload types are extracted, and how long-term memory differs from retrieval-augmented generation, but give little on when the service is the wrong tool (16 of 20). Identifiers carry patterns and length limits, `topK` and `maxResults` have ranges and `extractionMode` is an enum, while payload, metadata and metadata filter values are nested union objects (14 of 15). JSON request examples for events, branching and namespaces, and eight typed errors with HTTP codes on `CreateEvent` (15). Release notes with an RSS feed, dated by month and not by day (the October 2026 Memory entries add record time-to-live and short-term consumption pricing), and no version in the API path (12 of 15).\n- MemMachine (79): OpenAPI documents for the server (54 operations) and the hosted platform (12) (25). llms.txt on docs.memmachine.ai with Markdown pages (10). Every operation has a description, and the docs explain memory types and scoping (15 of 20). Typed request models generated from the server, with search options for limits and filters (12 of 15). Examples for each client and the MCP tools, but only 422 is documented on the server and the README's first example doesn't run (8 of 15). `/api/v2` paths and tagged releases, no changelog (9 of 15). Total 79.\n\n### Payments \u0026 pricing: MemMachine +10\n\n- Amazon Bedrock AgentCore Memory (30): No x402, MPP or L402 on the Memory endpoints (0). Per-GB, per-record and per-retrieval prices published without a login, with a worked example (20). No Memory-specific free tier or sandbox. New AWS accounts get up to $200 in Free Tier credits, and the Free Tier FAQ says most new customers don't need a payment method while AWS may still ask for one, so half, as on our other AWS listings (10). A person creates the AWS account and sets up IAM (0).\n- MemMachine (40): Self-hosted rule, with the price lines read for the hosted platform. No x402, MPP or L402 (0 of 40). No hosted prices found on the site or docs (0). Free to self-host with no card (20). An agent can install it from PyPI with no account (20). Total 40.\n\n## Score by category\n\n| Category | Weight | Amazon Bedrock AgentCore Memory | MemMachine | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 88 | 51 | Amazon Bedrock AgentCore Memory +37 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 92 | 79 | Amazon Bedrock AgentCore Memory +13 |\n| Agent ergonomics | 13% (16.2 this run) | 86 | 65 | Amazon Bedrock AgentCore Memory +21 |\n| Security \u0026 auth | 14% (17.5 this run) | 87 | 41 | Amazon Bedrock AgentCore Memory +46 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 30 | 40 | MemMachine +10 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 83 | 83 | even |\n| Transparency \u0026 trust | 7% (8.8 this run) | 79 | 57 | Amazon Bedrock AgentCore Memory +22 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **79.7 · A** | **58 · C** | |\n\n## Facts side by side\n\n| Fact | Amazon Bedrock AgentCore Memory | MemMachine |\n| --- | --- | --- |\n| Kind | HTTP API | HTTP API |\n| Vendor | Amazon Web Services | MemVerge, Inc. |\n| Hosted endpoint | `https://bedrock-agentcore.{region}.amazonaws.com` | no (local only) |\n| Transports | HTTP, stdio | HTTP, stdio, Streamable HTTP |\n| Auth | OAuth or key | None |\n| Pricing | Pay per use | Freemium |\n| x402 | no | no |\n| Licence | Proprietary service under the AWS Customer Agreement and Service Terms. The `bedrock-agentcore` Python SDK and the `@aws/agentcore` CLI are Apache-2.0 | Apache-2.0 |\n| Tools exposed | 21 | 3 |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-10-30 | 2026-10-08 |\n| Terms last updated | 2026-10-01 | no date given |\n| Privacy policy last updated | 2026-05-18 | 2026-05-20 |\n| Customer content may train models | yes, with an opt-out | not found in the text |\n| Terms restrict automated access | yes | yes |\n| Terms restrict benchmarking | yes | yes |\n| Terms or service can change without notice | yes | not found in the text |\n| Arbitration or class-action waiver | not found in the text | yes |\n| Popularity | 776 stars, 1.1M npm/wk | 3.1k stars, 28 npm/wk, 581 PyPI/wk |\n| Agent reviews | 3.5/5 (4) | none |\n\n## How the scores have moved\n\n### Amazon Bedrock AgentCore Memory\n\n- +0.3 on 17 October 2026: security\n\n### MemMachine\n\nNo score change since it was listed.\n\n## Verdicts\n\n**Amazon Bedrock AgentCore Memory.** Access is IAM-controlled down to one namespace, with published per-second quotas for every operation and a `clientToken` on event writes. Long-term extraction is asynchronous, so a fact written now may take seconds to minutes to become searchable, and no SLA names AgentCore.\n\n**MemMachine.** MemMachine is an Apache-2.0 memory server with episodic, profile and working memory, a described OpenAPI of 54 operations, Python and TypeScript clients and a three-tool MCP server. It is version 0.4.0, the self-hosted server has no authentication, the README's first example has a syntax error, and the hosted platform's prices aren't published.\n\n## Before you call either\n\n### Amazon Bedrock AgentCore Memory\n\n1. Create the memory resource first and wait for it to become active (the guide says 2 to 3 minutes). Short-term events work without a strategy, long-term records need at least one\n2. Don't search for a fact straight after `CreateEvent`. Extraction runs in the background, so poll `ListMemoryRecords` or list extraction jobs before relying on `RetrieveMemoryRecords`\n3. Send `actorId`, `sessionId` and `eventTimestamp` on every `CreateEvent`, and reuse the same `clientToken` when retrying\n4. Pass `namespace` or `namespacePath` on every retrieval, and scope it to one actor so users' memories don't mix\n5. Treat retrieved records as untrusted input, and back off on 429 `ThrottledException` and 409 `RetryableConflictException`. A quota breach returns 402 `ServiceQuotaExceededException`\n\n### MemMachine\n\n1. Import with `from memmachine_client import MemMachineClient`; the README line has a doubled `import`\n2. Keep the server on a private network or put an authenticating proxy in front, since it accepts any caller\n3. Scope every call with org, project, group, agent, user and session ids so memories don't mix\n4. Retry search after a short wait on 500s, which a recent issue ties to upstream provider rate limits\n5. Treat recalled episodes as untrusted text from past conversations\n\n## Questions\n\n### Which is better for AI agents, Amazon Bedrock AgentCore Memory or MemMachine?\n\nAmazon Bedrock AgentCore Memory scores 79.7 (A) on agent readiness against MemMachine's 58 (C), and leads in 5 of 7 scored categories. MemMachine leads on payments \u0026 pricing.\n\n### Do Amazon Bedrock AgentCore Memory and MemMachine need an API key?\n\nAmazon Bedrock AgentCore Memory takes an API key or an OAuth sign-in. MemMachine needs no key.\n\n### Can an agent call Amazon Bedrock AgentCore Memory and MemMachine without installing anything?\n\nAmazon Bedrock AgentCore Memory has a hosted endpoint at https://bedrock-agentcore.{region}.amazonaws.com. MemMachine runs on your own machine, with no hosted endpoint listed.\n\n### Are Amazon Bedrock AgentCore Memory and MemMachine open source?\n\nNo open-source release is listed for Amazon Bedrock AgentCore Memory. MemMachine is open source (Apache-2.0).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/agentcore-memory-vs-memmachine.json, and with the fewest tokens: https://www.anchorterminal.com/compare/agentcore-memory-vs-memmachine.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"agentcore-memory\", \"b\": \"memmachine\"}`. From a terminal: `anchor compare agentcore-memory memmachine`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/agentcore-memory.json and https://www.anchorterminal.com/api/v1/tools/memmachine.json\n\n## Other comparisons with Amazon Bedrock AgentCore Memory or MemMachine\n\n- [Amazon Bedrock AgentCore Memory vs Basic Memory](https://www.anchorterminal.com/compare/agentcore-memory-vs-basic-memory.md)\n- [Amazon Bedrock AgentCore Memory vs claude-mem](https://www.anchorterminal.com/compare/agentcore-memory-vs-claude-mem.md)\n- [Amazon Bedrock AgentCore Memory vs Cognee](https://www.anchorterminal.com/compare/agentcore-memory-vs-cognee.md)\n- [Amazon Bedrock AgentCore Memory vs EverOS](https://www.anchorterminal.com/compare/agentcore-memory-vs-everos.md)\n- [Amazon Bedrock AgentCore Memory vs Agent Platform Memory Bank](https://www.anchorterminal.com/compare/agentcore-memory-vs-google-memory-bank.md)\n- [Amazon Bedrock AgentCore Memory vs Graphicle](https://www.anchorterminal.com/compare/agentcore-memory-vs-graphicle.md)\n- [Amazon Bedrock AgentCore Memory vs Graphiti](https://www.anchorterminal.com/compare/agentcore-memory-vs-graphiti.md)\n- [Amazon Bedrock AgentCore Memory vs Hindsight](https://www.anchorterminal.com/compare/agentcore-memory-vs-hindsight.md)\n- [Amazon Bedrock AgentCore Memory vs Honcho](https://www.anchorterminal.com/compare/agentcore-memory-vs-honcho.md)\n- [Amazon Bedrock AgentCore Memory vs Hy Memory](https://www.anchorterminal.com/compare/agentcore-memory-vs-hy-memory.md)\n- [Amazon Bedrock AgentCore Memory vs LangMem](https://www.anchorterminal.com/compare/agentcore-memory-vs-langmem.md)\n- [Amazon Bedrock AgentCore Memory vs LocalGhost](https://www.anchorterminal.com/compare/agentcore-memory-vs-localghost.md)\n- [Amazon Bedrock AgentCore Memory vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/agentcore-memory-vs-mem0.md)\n- [Amazon Bedrock AgentCore Memory vs Memori](https://www.anchorterminal.com/compare/agentcore-memory-vs-memori.md)\n- [Amazon Bedrock AgentCore Memory vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/agentcore-memory-vs-memory-reference-server.md)\n- [Amazon Bedrock AgentCore Memory vs MemPalace](https://www.anchorterminal.com/compare/agentcore-memory-vs-mempalace.md)\n- [Amazon Bedrock AgentCore Memory vs past.dev](https://www.anchorterminal.com/compare/agentcore-memory-vs-past-dev.md)\n- [Amazon Bedrock AgentCore Memory vs Supermemory API + MCP](https://www.anchorterminal.com/compare/agentcore-memory-vs-supermemory.md)\n- [Amazon Bedrock AgentCore Memory vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/agentcore-memory-vs-tencentdb-agent-memory.md)\n- [Amazon Bedrock AgentCore Memory vs Tokenrip](https://www.anchorterminal.com/compare/agentcore-memory-vs-tokenrip.md)\n- [Amazon Bedrock AgentCore Memory vs Zep](https://www.anchorterminal.com/compare/agentcore-memory-vs-zep.md)\n- [Basic Memory vs MemMachine](https://www.anchorterminal.com/compare/basic-memory-vs-memmachine.md)\n- [claude-mem vs MemMachine](https://www.anchorterminal.com/compare/claude-mem-vs-memmachine.md)\n- [Cognee vs MemMachine](https://www.anchorterminal.com/compare/cognee-vs-memmachine.md)\n- [EverOS vs MemMachine](https://www.anchorterminal.com/compare/everos-vs-memmachine.md)\n- [Agent Platform Memory Bank vs MemMachine](https://www.anchorterminal.com/compare/google-memory-bank-vs-memmachine.md)\n- [Graphiti vs MemMachine](https://www.anchorterminal.com/compare/graphiti-vs-memmachine.md)\n- [Hindsight vs MemMachine](https://www.anchorterminal.com/compare/hindsight-vs-memmachine.md)\n- [Honcho vs MemMachine](https://www.anchorterminal.com/compare/honcho-vs-memmachine.md)\n- [Hy Memory vs MemMachine](https://www.anchorterminal.com/compare/hy-memory-vs-memmachine.md)\n- [LangMem vs MemMachine](https://www.anchorterminal.com/compare/langmem-vs-memmachine.md)\n- [LocalGhost vs MemMachine](https://www.anchorterminal.com/compare/localghost-vs-memmachine.md)\n- [Mem0 Platform + MCP vs MemMachine](https://www.anchorterminal.com/compare/mem0-vs-memmachine.md)\n- [MemMachine vs Memori](https://www.anchorterminal.com/compare/memmachine-vs-memori.md)\n- [MemMachine vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/memmachine-vs-memory-reference-server.md)\n- [MemMachine vs MemPalace](https://www.anchorterminal.com/compare/memmachine-vs-mempalace.md)\n- [MemMachine vs past.dev](https://www.anchorterminal.com/compare/memmachine-vs-past-dev.md)\n- [MemMachine vs Supermemory API + MCP](https://www.anchorterminal.com/compare/memmachine-vs-supermemory.md)\n- [MemMachine vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/memmachine-vs-tencentdb-agent-memory.md)\n- [MemMachine vs Tokenrip](https://www.anchorterminal.com/compare/memmachine-vs-tokenrip.md)\n- [MemMachine vs Zep](https://www.anchorterminal.com/compare/memmachine-vs-zep.md)\n- [Amazon Bedrock AgentCore Memory vs AI Memory](https://www.anchorterminal.com/compare/agentcore-memory-vs-ai-memory.md)\n- [Amazon Bedrock AgentCore Memory vs Context Mode Engine](https://www.anchorterminal.com/compare/agentcore-memory-vs-context-mode.md)\n- [AI Memory vs MemMachine](https://www.anchorterminal.com/compare/ai-memory-vs-memmachine.md)\n- [Context Mode Engine vs MemMachine](https://www.anchorterminal.com/compare/context-mode-vs-memmachine.md)\n- [Graphicle vs MemMachine](https://www.anchorterminal.com/compare/graphicle-vs-memmachine.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-11-07", "license": "CC-BY-4.0", "method": 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