{ "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": 1510, "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": "2026-11-07T22:55:43.559620626Z", "lastOk": false, "lastStatus": 0, "lastMs": 0, "lastNote": "invalid character \"{\" in host name", "authRequired": false, "uptime24h": 0, "uptime30d": 0, "p50ms24h": 0, "p95ms24h": 0, "samples24h": 244, "samples30d": 7335, "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": 233, "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": "2026-11-07T22:55:43.559620626Z" } }, "answer": "Amazon Bedrock AgentCore Memory scores 79.7 (A) on agent readiness against EverOS's 69.4 (B), and leads in 6 of 7 scored categories. EverOS leads on payments \u0026 pricing.", "b": { "slug": "everos", "name": "EverOS", "vendor": "Evermind AI, Inc.", "vendorUrl": "https://evermind.ai", "kind": "http-api", "category": "agent-memory", "summary": "EverOS, formerly EverMemOS, is EverMind's open-source memory runtime for agents. It stores conversations, files and agent trajectories as Markdown with SQLite and LanceDB indexes, behind a local HTTP API and MCP server, with a managed EverOS Cloud.", "url": "https://www.anchorterminal.com/tools/everos", "markdownUrl": "https://www.anchorterminal.com/tools/everos.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/everos.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/everos.json", "dns": "everos.grade.anchorterminal.com", "repo": "https://github.com/EverMind-AI/EverOS", "license": "Apache-2.0", "transports": [ "http", "stdio" ], "packages": [ { "registry": "pypi", "name": "everos" }, { "registry": "pypi", "name": "everos-mcp" } ], "auth": "none", "authNotes": "The self-hosted server has no authentication and binds to 127.0.0.1:8000 by default. The owner supplies LLM and embedding provider keys in ~/.everos/everos.toml. EverOS Cloud uses a bearer API key from the console at everos.evermind.ai, and its hosted MCP connector signs in with an EverOS account.", "pricing": "freemium", "pricingNotes": "Free under Apache-2.0 to run locally, with LLM and embedding costs paid to the chosen provider. EverOS Cloud has a console and API keys, but no plan or price was found on evermind.ai or docs.evermind.ai.", "priceSummary": "Freemium", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the repository, the OpenAPI document, llms.txt or the docs (checked 2026-11-06).", "endpoints": [] }, "toolCount": 7, "popularity": { "githubStars": 13839, "npmWeekly": null, "pypiWeekly": 4033, "asOf": "2026-11-06" }, "docsUrl": "https://docs.evermind.ai", "llmsTxt": "https://docs.evermind.ai/llms.txt", "openapi": "https://github.com/EverMind-AI/EverOS/blob/main/docs/openapi.json", "capabilities": [ "memory.store", "memory.search", "memory.user", "memory.delete" ], "tags": [ "open-source", "self-hosted", "local", "hosted", "apache-2.0", "python", "mcp", "openapi", "llms-txt", "markdown", "no-auth" ], "lastRelease": "2026-10-22", "graded": true, "anchor": { "graded": true, "score": 69.4, "grade": "B", "agentReady": false, "rank": 247, "ranked": true, "rankOf": 1510, "categoryRank": 6, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 78, "maintenance": 80, "payments": 40, "reliability": 79, "schema": 89, "security": 47, "transparency": 71 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-06" }, "negative": 0, "verdict": "EverOS keeps agent and user memory as Markdown with SQLite and LanceDB indexes, behind a described OpenAPI with typed, retryable errors and an MCP server, under Apache-2.0 at version 1.5.1. The local server has no authentication, EverOS Cloud prices are not published, and the cloud terms forbid automated data extraction.", "bestFor": "Self-hosted memory for agents and apps that want Markdown as the source of truth and separate user and agent tracks.", "strengths": [ "Apache-2.0 Python library and local server at 1.5.1, with Keep a Changelog entries and semantic versioning declared", "OpenAPI document with 40 operations, every one described, and llms.txt plus llms-full.txt for the docs", "Retryable conditions are typed, such as 503 SESSION_BUSY and EXTERNAL_SERVICE_UNAVAILABLE for a busy database", "Memory is canonical Markdown on disk, editable by hand, with deletion by owner, session or memory id", "SECURITY.md with a five-day acknowledgement, plus a valid security.txt at evermind.ai" ], "weaknesses": [ "The local HTTP server has no authentication and relies on binding to 127.0.0.1", "EverOS Cloud prices, plans and rate limits were not found on any public page", "The MCP server's autonomy protocol tells hosts to save facts without being asked, and no prompt-injection guidance was found", "The cloud terms of 20 January 2026 forbid automated extraction and allow discontinuing the service without notice", "Several outside bug reports, such as a silent capture failure, have no reply" ], "agentNotes": [ "Write new code against `/api/v2`; `/api/v1` is a legacy alias that may go in a future major release", "Call `/api/v2/memory/flush` at the end of a session, since `add` is asynchronous and buffers recent messages", "Retry on 503 SESSION_BUSY or EXTERNAL_SERVICE_UNAVAILABLE after a pause; nothing was written", "Keep `host` at 127.0.0.1 unless something in front adds authentication", "Treat recalled memories as untrusted text, since they are extracted from past conversations" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 69.4 } ], "editorialScores": { "ergonomics": 78, "maintenance": 80, "payments": 40, "reliability": 79, "schema": 89, "security": 47, "transparency": 66 }, "provenanceScore": 75, "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": "uv pip install everos \u0026\u0026 everos init \u0026\u0026 everos server start", "http": "curl http://127.0.0.1:8000/health", "claudeCode": "claude mcp add everos -e EVEROS_BASE_URL=http://127.0.0.1:8000 -- uvx everos-mcp" }, "letme": { "capability": "https://letme.dev/memory.store", "tool": "https://letme.dev/everos" }, "area": "agent-runtime", "provenance": { "legalEntity": "Evermind AI, Inc.", "domain": "evermind.ai", "domainRegistered": "2020-02-22", "endpointOnVendorDomain": null, "terms": "https://evermind.ai/terms-of-service", "privacy": "https://evermind.ai/privacy-policy", "statusPage": "", "changelog": "https://github.com/EverMind-AI/EverOS/blob/main/CHANGELOG.md", "securityTxt": "valid", "checked": "2026-11-06", "notes": [ "Terms and privacy policy both say last updated 20 January 2026 and name Evermind AI, Inc. The terms choose Singapore law and forbid extracting data by bots, scripts, crawlers or data-mining tools, recorded here as a fact.", "evermind.ai/robots.txt allows all crawlers and names Claude-Web and anthropic-ai as allowed. docs.evermind.ai carries Content-Signal ai-input=yes.", "RDAP gives evermind.ai a registration date of 22 February 2020.", "security.txt at evermind.ai/.well-known/ gives contact@evermind.ai and a policy URL, expiring 28 February 2027.", "The about page is drawn by script and returned no readable text." ], "score": 75 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/everos.json", "live": { "slug": "everos", "versions": [ { "registry": "github", "name": "EverMind-AI/EverOS", "version": "v1.5.1", "released": "2026-10-22", "seenAt": "2026-11-06T23:24:44.540703115Z" }, { "registry": "pypi", "name": "everos", "version": "1.5.1", "released": "2026-10-22", "seenAt": "2026-11-06T23:24:41.488069905Z" }, { "registry": "pypi", "name": "everos-mcp", "version": "0.1.1", "released": "2026-10-15", "seenAt": "2026-11-06T23:24:42.65503941Z" } ], "githubStars": 13840, "pypiWeekly": 4033, "securityTxt": { "url": "https://evermind.ai/.well-known/security.txt", "state": "valid", "expires": "2027-02-28T00:00:00Z", "checkedAt": "2026-11-07T16:01:32.419431813Z" }, "llmsTxt": { "url": "https://docs.evermind.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:32:26.933711899Z" }, "pages": [ { "url": "https://raw.githubusercontent.com/EverMind-AI/EverOS/main/CHANGELOG.md", "kind": "changelog", "status": 200, "checkedAt": "2026-11-07T14:18:19.185692468Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "40ab92cf4d99" }, { "url": "https://evermind.ai/privacy-policy", "kind": "privacy", "status": 200, "checkedAt": "2026-11-07T14:09:24.819286526Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "dcd843ca72fe" }, { "url": "https://evermind.ai/terms-of-service", "kind": "terms", "status": 200, "checkedAt": "2026-11-07T14:09:28.72898661Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "009377ab61a3" } ], "updatedAt": "2026-11-07T16:01:32.419431813Z" } }, "edges": [ { "by": 40, "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 local server has no authentication and no security scheme in the OpenAPI document, relying on a 127.0.0.1 bind by default (15 of 30). No read-only mode; the cloud purge is two-step (8 of 20). Memories are extracted from conversations and returned into prompts, and everos-mcp tells hosts to save facts unprompted, with no injection guidance found (4 of 15). Structured logs and lock metrics, no audit log (6 of 15). SECURITY.md with a reporting address, five-day acknowledgement, supported versions and a published-advisories section, plus a valid security.txt (14 of 20). Total 47." }, "scores": { "a": 87, "b": 47 } }, { "by": 10, "category": "payments", "leads": "everos", "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 EverOS Cloud. No x402, MPP or L402 (0 of 40). No cloud price or plan found on evermind.ai, its FAQ, terms or docs (0). The open-source runtime is free with no card (20). An agent can install it from PyPI and run it with no account (20). Total 40." }, "scores": { "a": 30, "b": 40 } }, { "by": 9, "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 library and server the owner runs. `everos` on PyPI with Python 3.12 or newer stated, plus a Windows guide (20). ci.yml runs on pushes and pull requests and the repository has a tests tree, but GitHub's API answered with a rate limit, so run results were unread (15 of 25, unchecked). 43 open issues and pull requests against 82 commits in 90 days; several outside bug reports, including a silent capture failure in the DSH plugin, have no reply (14 of 25). Keep a Changelog with semantic versioning declared and a 1.0 migration guide (15). Version 1.5.1 (15). Total 79." }, "scores": { "a": 88, "b": 79 } }, { "by": 8, "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": "Read for the API, with seven MCP tools on top. Searches take `top_k` and a method, and responses can be scoped by five ids (20 of 25). Filters nest with AND and OR, and `/get` pages results (18 of 20). Errors carry typed codes and say which are retryable (16 of 20). `add` is queued and returns 202, a busy session refuses deletion with nothing deleted, and the cloud purge needs a nonce confirmed within five minutes (12 of 20). A demo runs with no key and the minimal setup needs one OpenRouter key, with a Python library and the MCP server, one language (12 of 15). Total 78." }, "scores": { "a": 86, "b": 78 } }, { "by": 8, "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 with a NOTICE file (30). Local data stays in the owner's Markdown and indexes. For the cloud, the privacy policy gives no retention periods, the terms and privacy policy word the training exceptions differently, and the privacy contact link points to a miromind.ai address (12 of 30). The README marks `/api/v1` as a legacy alias that may be removed in a future major release, and a 1.0 migration guide exists, with no notice period (14 of 20). No outbound telemetry was found in the source, and the docs don't address it (10 of 20). Total 66." }, "scores": { "a": 79, "b": 71 } } ], "facts": [ { "a": "HTTP API", "b": "HTTP API", "name": "Kind" }, { "a": "Amazon Web Services", "b": "Evermind AI, Inc.", "name": "Vendor" }, { "a": "https://bedrock-agentcore.{region}.amazonaws.com", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "HTTP, stdio", "b": "HTTP, stdio", "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": "7", "name": "Tools exposed" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-30", "b": "2026-10-22", "name": "Last release" }, { "a": "2026-10-01", "b": "2026-01-20", "name": "Terms last updated" }, { "a": "2026-05-18", "b": "2026-01-20", "name": "Privacy policy last updated" }, { "a": "yes, with an opt-out", "b": "yes", "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": "yes", "name": "Terms or service can change without notice" }, { "a": "not found in the text", "b": "not found in the text", "name": "Arbitration or class-action waiver" }, { "a": "776 stars, 1.1M npm/wk", "b": "14k stars, 4k 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 EverOS's 69.4 (B), and leads in 6 of 7 scored categories. EverOS leads on payments \u0026 pricing.", "question": "Which is better for AI agents, Amazon Bedrock AgentCore Memory or EverOS?" }, { "answer": "Amazon Bedrock AgentCore Memory takes an API key or an OAuth sign-in. EverOS needs no key.", "question": "Do Amazon Bedrock AgentCore Memory and EverOS need an API key?" }, { "answer": "Amazon Bedrock AgentCore Memory has a hosted endpoint at https://bedrock-agentcore.{region}.amazonaws.com. EverOS runs on your own machine, with no hosted endpoint listed.", "question": "Can an agent call Amazon Bedrock AgentCore Memory and EverOS without installing anything?" }, { "answer": "No open-source release is listed for Amazon Bedrock AgentCore Memory. EverOS is open source (Apache-2.0).", "question": "Are Amazon Bedrock AgentCore Memory and EverOS open source?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 88 against 79", "Agent ergonomics, 86 against 78", "Security \u0026 auth, 87 against 47", "Transparency \u0026 trust, 79 against 71" ], "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 agents and apps that want Markdown as the source of truth and separate user and agent tracks.", "slug": "everos", "watchFor": "The local HTTP server has no authentication and relies on binding to 127.0.0.1" } ], "history": { "agentcore-memory": [ { "causes": [ "security" ], "date": "2026-10-17", "delta": 0.3, "from": 79.4, "fromGrade": "A", "to": 79.7, "toGrade": "A" } ], "everos": 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-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-memmachine.json", "title": "Amazon Bedrock AgentCore Memory vs MemMachine", "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-memmachine" }, { "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-everos.json", "title": "Basic Memory vs EverOS", "url": "https://www.anchorterminal.com/compare/basic-memory-vs-everos" }, { "json": "https://www.anchorterminal.com/compare/claude-mem-vs-everos.json", "title": "claude-mem vs EverOS", "url": "https://www.anchorterminal.com/compare/claude-mem-vs-everos" }, { "json": "https://www.anchorterminal.com/compare/cognee-vs-everos.json", "title": "Cognee vs EverOS", "url": "https://www.anchorterminal.com/compare/cognee-vs-everos" }, { "json": "https://www.anchorterminal.com/compare/everos-vs-google-memory-bank.json", "title": "EverOS vs Agent Platform Memory Bank", "url": "https://www.anchorterminal.com/compare/everos-vs-google-memory-bank" }, { "json": "https://www.anchorterminal.com/compare/everos-vs-graphicle.json", "title": "EverOS vs Graphicle", "url": "https://www.anchorterminal.com/compare/everos-vs-graphicle" }, { "json": "https://www.anchorterminal.com/compare/everos-vs-graphiti.json", "title": "EverOS vs Graphiti", "url": "https://www.anchorterminal.com/compare/everos-vs-graphiti" }, { "json": "https://www.anchorterminal.com/compare/everos-vs-hindsight.json", "title": "EverOS vs Hindsight", "url": "https://www.anchorterminal.com/compare/everos-vs-hindsight" }, { "json": "https://www.anchorterminal.com/compare/everos-vs-honcho.json", "title": "EverOS vs Honcho", "url": "https://www.anchorterminal.com/compare/everos-vs-honcho" }, { "json": "https://www.anchorterminal.com/compare/everos-vs-hy-memory.json", "title": "EverOS vs Hy Memory", "url": "https://www.anchorterminal.com/compare/everos-vs-hy-memory" }, { "json": "https://www.anchorterminal.com/compare/everos-vs-langmem.json", "title": "EverOS vs LangMem", "url": "https://www.anchorterminal.com/compare/everos-vs-langmem" }, { "json": "https://www.anchorterminal.com/compare/everos-vs-localghost.json", "title": "EverOS vs LocalGhost", "url": "https://www.anchorterminal.com/compare/everos-vs-localghost" }, { "json": "https://www.anchorterminal.com/compare/everos-vs-mem0.json", "title": "EverOS vs Mem0 Platform + MCP", "url": "https://www.anchorterminal.com/compare/everos-vs-mem0" }, { "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/everos-vs-memori.json", "title": "EverOS vs Memori", "url": "https://www.anchorterminal.com/compare/everos-vs-memori" }, { "json": "https://www.anchorterminal.com/compare/everos-vs-memory-reference-server.json", "title": "EverOS vs Memory (MCP reference server)", "url": "https://www.anchorterminal.com/compare/everos-vs-memory-reference-server" }, { "json": "https://www.anchorterminal.com/compare/everos-vs-mempalace.json", "title": "EverOS vs MemPalace", "url": "https://www.anchorterminal.com/compare/everos-vs-mempalace" }, { "json": "https://www.anchorterminal.com/compare/everos-vs-past-dev.json", "title": "EverOS vs past.dev", "url": "https://www.anchorterminal.com/compare/everos-vs-past-dev" }, { "json": "https://www.anchorterminal.com/compare/everos-vs-supermemory.json", "title": "EverOS vs Supermemory API + MCP", "url": "https://www.anchorterminal.com/compare/everos-vs-supermemory" }, { "json": "https://www.anchorterminal.com/compare/everos-vs-tencentdb-agent-memory.json", "title": "EverOS vs TencentDB Agent Memory", "url": "https://www.anchorterminal.com/compare/everos-vs-tencentdb-agent-memory" }, { "json": "https://www.anchorterminal.com/compare/everos-vs-tokenrip.json", "title": "EverOS vs Tokenrip", "url": "https://www.anchorterminal.com/compare/everos-vs-tokenrip" }, { "json": "https://www.anchorterminal.com/compare/everos-vs-zep.json", "title": "EverOS vs Zep", "url": "https://www.anchorterminal.com/compare/everos-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-everos.json", "title": "AI Memory vs EverOS", "url": "https://www.anchorterminal.com/compare/ai-memory-vs-everos" }, { "json": "https://www.anchorterminal.com/compare/context-mode-vs-everos.json", "title": "Context Mode Engine vs EverOS", "url": "https://www.anchorterminal.com/compare/context-mode-vs-everos" } ], "panel": null, "scores": [ { "agentcore-memory": 88, "by": 9, "edge": "agentcore-memory", "everos": 79, "key": "reliability", "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "agentcore-memory": 92, "by": 3, "edge": "agentcore-memory", "everos": 89, "key": "schema", "name": "Schema \u0026 documentation", "weight": 13 }, { "agentcore-memory": 86, "by": 8, "edge": "agentcore-memory", "everos": 78, "key": "ergonomics", "name": "Agent ergonomics", "weight": 13 }, { "agentcore-memory": 87, "by": 40, "edge": "agentcore-memory", "everos": 47, "key": "security", "name": "Security \u0026 auth", "weight": 14 }, { "agentcore-memory": 30, "by": 10, "edge": "everos", "everos": 40, "key": "payments", "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "agentcore-memory": 83, "by": 3, "edge": "agentcore-memory", "everos": 80, "key": "maintenance", "name": "Maintenance \u0026 community", "weight": 7 }, { "agentcore-memory": 79, "by": 8, "edge": "agentcore-memory", "everos": 71, "key": "transparency", "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Amazon Bedrock AgentCore Memory scores 79.7 (A) on agent readiness against EverOS's 69.4 (B), and leads in 6 of 7 scored categories. EverOS 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.", "everos": "EverOS keeps agent and user memory as Markdown with SQLite and LanceDB indexes, behind a described OpenAPI with typed, retryable errors and an MCP server, under Apache-2.0 at version 1.5.1. The local server has no authentication, EverOS Cloud prices are not published, and the cloud terms forbid automated data extraction." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/agentcore-memory-vs-everos", "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-everos.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/agentcore-memory-vs-everos.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/agentcore-memory-vs-everos.min.md" }, "markdown": "Amazon Bedrock AgentCore Memory scores 79.7 (A) on agent readiness against EverOS's 69.4 (B), and leads in 6 of 7 scored categories. EverOS leads on payments \u0026 pricing. Both do agent memory.\n\n- Amazon Bedrock AgentCore Memory: grade A, 79.7/100, rank #17 of 1510. Markdown https://www.anchorterminal.com/tools/agentcore-memory.md · JSON https://www.anchorterminal.com/api/v1/tools/agentcore-memory.json\n- EverOS: grade B, 69.4/100, rank #247 of 1510. Markdown https://www.anchorterminal.com/tools/everos.md · JSON https://www.anchorterminal.com/api/v1/tools/everos.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 79\n- Agent ergonomics, 86 against 78\n- Security \u0026 auth, 87 against 47\n- Transparency \u0026 trust, 79 against 71\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### EverOS (B)\n\nGood for: Self-hosted memory for agents and apps that want Markdown as the source of truth and separate user and agent tracks.\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: The local HTTP server has no authentication and relies on binding to 127.0.0.1\n\n\n## Why the edge\n\n### Security \u0026 auth: Amazon Bedrock AgentCore Memory +40\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- EverOS (47): Framework reading for software the owner runs. The local server has no authentication and no security scheme in the OpenAPI document, relying on a 127.0.0.1 bind by default (15 of 30). No read-only mode; the cloud purge is two-step (8 of 20). Memories are extracted from conversations and returned into prompts, and everos-mcp tells hosts to save facts unprompted, with no injection guidance found (4 of 15). Structured logs and lock metrics, no audit log (6 of 15). SECURITY.md with a reporting address, five-day acknowledgement, supported versions and a published-advisories section, plus a valid security.txt (14 of 20). Total 47.\n\n### Payments \u0026 pricing: EverOS +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- EverOS (40): Self-hosted rule, with the price lines read for EverOS Cloud. No x402, MPP or L402 (0 of 40). No cloud price or plan found on evermind.ai, its FAQ, terms or docs (0). The open-source runtime is free with no card (20). An agent can install it from PyPI and run it with no account (20). Total 40.\n\n### Reliability: Amazon Bedrock AgentCore Memory +9\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- EverOS (79): Local-software lines, as a library and server the owner runs. `everos` on PyPI with Python 3.12 or newer stated, plus a Windows guide (20). ci.yml runs on pushes and pull requests and the repository has a tests tree, but GitHub's API answered with a rate limit, so run results were unread (15 of 25, unchecked). 43 open issues and pull requests against 82 commits in 90 days; several outside bug reports, including a silent capture failure in the DSH plugin, have no reply (14 of 25). Keep a Changelog with semantic versioning declared and a 1.0 migration guide (15). Version 1.5.1 (15). Total 79.\n\n### Agent ergonomics: Amazon Bedrock AgentCore Memory +8\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- EverOS (78): Read for the API, with seven MCP tools on top. Searches take `top_k` and a method, and responses can be scoped by five ids (20 of 25). Filters nest with AND and OR, and `/get` pages results (18 of 20). Errors carry typed codes and say which are retryable (16 of 20). `add` is queued and returns 202, a busy session refuses deletion with nothing deleted, and the cloud purge needs a nonce confirmed within five minutes (12 of 20). A demo runs with no key and the minimal setup needs one OpenRouter key, with a Python library and the MCP server, one language (12 of 15). Total 78.\n\n### Transparency \u0026 trust: Amazon Bedrock AgentCore Memory +8\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- EverOS (71): Apache-2.0 with a NOTICE file (30). Local data stays in the owner's Markdown and indexes. For the cloud, the privacy policy gives no retention periods, the terms and privacy policy word the training exceptions differently, and the privacy contact link points to a miromind.ai address (12 of 30). The README marks `/api/v1` as a legacy alias that may be removed in a future major release, and a 1.0 migration guide exists, with no notice period (14 of 20). No outbound telemetry was found in the source, and the docs don't address it (10 of 20). Total 66.\n\n## Score by category\n\n| Category | Weight | Amazon Bedrock AgentCore Memory | EverOS | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 88 | 79 | Amazon Bedrock AgentCore Memory +9 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 92 | 89 | Amazon Bedrock AgentCore Memory +3 |\n| Agent ergonomics | 13% (16.2 this run) | 86 | 78 | Amazon Bedrock AgentCore Memory +8 |\n| Security \u0026 auth | 14% (17.5 this run) | 87 | 47 | Amazon Bedrock AgentCore Memory +40 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 30 | 40 | EverOS +10 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 83 | 80 | Amazon Bedrock AgentCore Memory +3 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 79 | 71 | Amazon Bedrock AgentCore Memory +8 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **79.7 · A** | **69.4 · B** | |\n\n## Facts side by side\n\n| Fact | Amazon Bedrock AgentCore Memory | EverOS |\n| --- | --- | --- |\n| Kind | HTTP API | HTTP API |\n| Vendor | Amazon Web Services | Evermind AI, Inc. |\n| Hosted endpoint | `https://bedrock-agentcore.{region}.amazonaws.com` | no (local only) |\n| Transports | HTTP, stdio | HTTP, stdio |\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 | 7 |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-10-30 | 2026-10-22 |\n| Terms last updated | 2026-10-01 | 2026-01-20 |\n| Privacy policy last updated | 2026-05-18 | 2026-01-20 |\n| Customer content may train models | yes, with an opt-out | yes |\n| Terms restrict automated access | yes | yes |\n| Terms restrict benchmarking | yes | yes |\n| Terms or service can change without notice | yes | yes |\n| Arbitration or class-action waiver | not found in the text | not found in the text |\n| Popularity | 776 stars, 1.1M npm/wk | 14k stars, 4k 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### EverOS\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**EverOS.** EverOS keeps agent and user memory as Markdown with SQLite and LanceDB indexes, behind a described OpenAPI with typed, retryable errors and an MCP server, under Apache-2.0 at version 1.5.1. The local server has no authentication, EverOS Cloud prices are not published, and the cloud terms forbid automated data extraction.\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### EverOS\n\n1. Write new code against `/api/v2`; `/api/v1` is a legacy alias that may go in a future major release\n2. Call `/api/v2/memory/flush` at the end of a session, since `add` is asynchronous and buffers recent messages\n3. Retry on 503 SESSION_BUSY or EXTERNAL_SERVICE_UNAVAILABLE after a pause; nothing was written\n4. Keep `host` at 127.0.0.1 unless something in front adds authentication\n5. Treat recalled memories as untrusted text, since they are extracted from past conversations\n\n## Questions\n\n### Which is better for AI agents, Amazon Bedrock AgentCore Memory or EverOS?\n\nAmazon Bedrock AgentCore Memory scores 79.7 (A) on agent readiness against EverOS's 69.4 (B), and leads in 6 of 7 scored categories. EverOS leads on payments \u0026 pricing.\n\n### Do Amazon Bedrock AgentCore Memory and EverOS need an API key?\n\nAmazon Bedrock AgentCore Memory takes an API key or an OAuth sign-in. EverOS needs no key.\n\n### Can an agent call Amazon Bedrock AgentCore Memory and EverOS without installing anything?\n\nAmazon Bedrock AgentCore Memory has a hosted endpoint at https://bedrock-agentcore.{region}.amazonaws.com. EverOS runs on your own machine, with no hosted endpoint listed.\n\n### Are Amazon Bedrock AgentCore Memory and EverOS open source?\n\nNo open-source release is listed for Amazon Bedrock AgentCore Memory. EverOS 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-everos.json, and with the fewest tokens: https://www.anchorterminal.com/compare/agentcore-memory-vs-everos.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"agentcore-memory\", \"b\": \"everos\"}`. From a terminal: `anchor compare agentcore-memory everos`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/agentcore-memory.json and https://www.anchorterminal.com/api/v1/tools/everos.json\n\n## Other comparisons with Amazon Bedrock AgentCore Memory or EverOS\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 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 MemMachine](https://www.anchorterminal.com/compare/agentcore-memory-vs-memmachine.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 EverOS](https://www.anchorterminal.com/compare/basic-memory-vs-everos.md)\n- [claude-mem vs EverOS](https://www.anchorterminal.com/compare/claude-mem-vs-everos.md)\n- [Cognee vs EverOS](https://www.anchorterminal.com/compare/cognee-vs-everos.md)\n- [EverOS vs Agent Platform Memory Bank](https://www.anchorterminal.com/compare/everos-vs-google-memory-bank.md)\n- [EverOS vs Graphicle](https://www.anchorterminal.com/compare/everos-vs-graphicle.md)\n- [EverOS vs Graphiti](https://www.anchorterminal.com/compare/everos-vs-graphiti.md)\n- [EverOS vs Hindsight](https://www.anchorterminal.com/compare/everos-vs-hindsight.md)\n- [EverOS vs Honcho](https://www.anchorterminal.com/compare/everos-vs-honcho.md)\n- [EverOS vs Hy Memory](https://www.anchorterminal.com/compare/everos-vs-hy-memory.md)\n- [EverOS vs LangMem](https://www.anchorterminal.com/compare/everos-vs-langmem.md)\n- [EverOS vs LocalGhost](https://www.anchorterminal.com/compare/everos-vs-localghost.md)\n- [EverOS vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/everos-vs-mem0.md)\n- [EverOS vs MemMachine](https://www.anchorterminal.com/compare/everos-vs-memmachine.md)\n- [EverOS vs Memori](https://www.anchorterminal.com/compare/everos-vs-memori.md)\n- [EverOS vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/everos-vs-memory-reference-server.md)\n- [EverOS vs MemPalace](https://www.anchorterminal.com/compare/everos-vs-mempalace.md)\n- [EverOS vs past.dev](https://www.anchorterminal.com/compare/everos-vs-past-dev.md)\n- [EverOS vs Supermemory API + MCP](https://www.anchorterminal.com/compare/everos-vs-supermemory.md)\n- [EverOS vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/everos-vs-tencentdb-agent-memory.md)\n- [EverOS vs Tokenrip](https://www.anchorterminal.com/compare/everos-vs-tokenrip.md)\n- [EverOS vs Zep](https://www.anchorterminal.com/compare/everos-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 EverOS](https://www.anchorterminal.com/compare/ai-memory-vs-everos.md)\n- [Context Mode Engine vs EverOS](https://www.anchorterminal.com/compare/context-mode-vs-everos.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": "https://www.anchorterminal.com/benchmark/", "methodology": "0.7", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run", "terms": 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