{ "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", "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": "2026-10-06", "graded": true, "anchor": { "graded": true, "score": 79.4, "grade": "A", "agentReady": true, "rank": 12, "ranked": true, "rankOf": 842, "categoryRank": 1, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 86, "maintenance": 83, "payments": 30, "reliability": 88, "schema": 92, "security": 87, "transparency": 76 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-08" }, "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, and events expire on a set time to live of 7 to 365 days" ], "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": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "A", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 79.4 } ], "editorialScores": { "ergonomics": 86, "maintenance": 83, "payments": 30, "reliability": 88, "schema": 92, "security": 87, "transparency": 64 }, "provenanceScore": 88 }, "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-nova-embeddings", "amazon-bedrock-guardrails", "amazon-transcribe", "amazon-polly", "agentcore-identity", "aws-secrets-manager", "aws-mcp-servers", "amazon-ses", "amazon-location", "amazon-translate", "amazon-ads-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": "expired", "checked": "2026-10-08", "notes": [ "The AWS Service Terms show Last Updated 1 October 2026. 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 shows Last Updated 18 May 2026.", "aws.amazon.com/.well-known/security.txt carries Expires 2026-09-24T16:25:03.000Z, so it was expired on 8 October 2026. It points to the vulnerability disclosure programme on HackerOne and the policy at vdp.aws.security.", "health.aws.amazon.com/health/status is drawn by script. The Bedrock AgentCore feed for us-east-1 had no items on 8 October 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.", "aws.amazon.com/bedrock/agentcore/sla/ returns 404 and the AWS SLA index does not name AgentCore." ], "score": 88 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/agentcore-memory.json", "live": { "slug": "agentcore-memory", "probe": { "target": "https://bedrock-agentcore.{region}.amazonaws.com", "method": "get", "lastAt": "2026-10-09T10:14:06.863477896Z", "lastOk": false, "lastStatus": 0, "lastMs": 0, "lastNote": "invalid character \"{\" in host name", "authRequired": false, "uptime24h": 0, "uptime30d": 0, "p50ms24h": 0, "p95ms24h": 0, "samples24h": 28, "samples30d": 28, "days": [ { "date": "2026-10-09", "probes": 28, "ok": 0 } ], "outages": [ { "start": "2026-10-09T07:40:18.334133541Z", "end": "0001-01-01T00:00:00Z", "note": "invalid character \"{\" in host name" } ] }, "updatedAt": "2026-10-09T10:14:06.863477896Z" } }, "answer": "Amazon Bedrock AgentCore Memory scores 79.4 (A) on agent readiness against Supermemory API + MCP's 63.6 (B), and leads in 5 of 7 scored categories.", "b": { "slug": "supermemory", "name": "Supermemory API + MCP", "vendor": "Supermemory", "vendorUrl": "https://supermemory.ai", "kind": "http-api", "category": "agent-memory", "summary": "Memory and context API that ingests text, URLs, PDFs, images and video, extracts memories into a graph per container tag (usually one per user) and returns them through search or a user profile endpoint.", "url": "https://www.anchorterminal.com/tools/supermemory", "markdownUrl": "https://www.anchorterminal.com/tools/supermemory.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/supermemory.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/supermemory.json", "repo": "https://github.com/supermemoryai/supermemory", "license": "MIT", "transports": [ "http", "streamable-http" ], "remoteUrl": "https://api.supermemory.ai", "packages": [ { "registry": "npm", "name": "supermemory" }, { "registry": "pypi", "name": "supermemory" } ], "auth": "mixed", "authNotes": "Bearer API key (`sm_...`) from console.supermemory.ai. Org keys have full access. Scoped keys are limited to one or more container tags, can't read billing, change settings or mint keys, can expire after 1 to 365 days and are revocable. The hosted MCP at mcp.supermemory.ai/mcp signs in with OAuth in a browser and needs no key.", "pricing": "freemium", "pricingNotes": "Each plan includes monthly usage credit. Free is $0 with $5 of credit, Pro $19 with $20, Max $100 with $130 (adds the Gmail connector), Scale $399 with $600 (adds PDF extraction, S3 and crawler connectors, SOC 2, a HIPAA BAA and a self-hosted option), and Enterprise is committed spend. Usage is $5 per million SM tokens for plain-text memory and $10 for rich content, $1 and $2 per million for SuperRAG text and rich media, $5 per million search queries and $100 per million operations (https://supermemory.ai/pricing). Paid plans can auto top up, and the top-up limits don't cap the invoice (https://supermemory.ai/docs/overview/billing.md).", "priceSummary": "$19 / mo", "where": "hosted", "x402": { "level": "no", "endpoints": [] }, "toolCount": 8, "popularity": { "githubStars": 31000, "npmWeekly": 121387, "pypiWeekly": 45053, "asOf": "2026-09-30" }, "docsUrl": "https://supermemory.ai/docs", "llmsTxt": "https://supermemory.ai/docs/llms.txt", "openapi": "https://api.supermemory.ai/v4/openapi", "capabilities": [ "memory.store", "memory.search", "memory.graph", "memory.user", "memory.delete" ], "tags": [ "hosted", "freemium", "free-tier", "mcp", "oauth", "llms-txt", "openapi", "python", "typescript", "open-source", "self-hosted", "enterprise" ], "lastRelease": "2026-09-21", "graded": true, "anchor": { "graded": true, "score": 63.6, "grade": "B", "agentReady": false, "rank": 348, "ranked": true, "rankOf": 842, "categoryRank": 4, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 73, "maintenance": 85, "payments": 30, "reliability": 65, "schema": 85, "security": 54, "transparency": 49 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-01" }, "negative": 0, "verdict": "8-tool hosted MCP with OAuth and per-space read or write permission. No legal entity named in the terms or privacy policy.", "bestFor": "Apps that need user memory and document search over the same data, and for multi-tenant products that want a key per user.", "strengths": [ "8-tool hosted MCP with OAuth and per-space read or write permission", "Scoped keys limited to container tags, with expiry from 1 to 365 days", "Status page shows 100 per cent for the API and Console from July to October 2026", "Customer content never trains models on any plan, per the security page", "One endpoint ingests text, URLs, PDFs, images and video" ], "weaknesses": [ "No legal entity named in the terms or privacy policy", "No published rate limits or 429 guidance", "Ingests web pages and PDFs with no prompt-injection guidance found", "v3 and v4 endpoints live side by side, so examples disagree", "No security.txt and no official MCP registry entry" ], "agentNotes": [ "Use one stable `containerTag` per user and a `customId` per session", "Poll the document until `status` is `done` before searching for what you just added", "Treat a 402 on search or profile as out of credit, not as a bug", "Run the prompt-based mass forget with `dryRun` first", "Call who_am_i on the MCP to see which spaces you can write to before adding" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 2, "avgRating": 3.5, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 63.6 } ], "editorialScores": { "ergonomics": 73, "maintenance": 85, "payments": 30, "reliability": 65, "schema": 85, "security": 54, "transparency": 43 }, "provenanceScore": 55 }, "connect": { "install": "npm install supermemory # or: pip install supermemory", "http": "curl -X POST \"https://api.supermemory.ai/v3/documents\" \\\n -H \"Authorization: Bearer $SUPERMEMORY_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\"content\":\"Sarah is being promoted to VP of Product.\",\"containerTag\":\"user_123\",\"customId\":\"chat_session_1\",\"metadata\":{\"type\":\"conversation\"},\"dreaming\":\"instant\"}'", "claudeCode": "claude mcp add --transport http supermemory https://mcp.supermemory.ai/mcp", "config": { "mcpServers": { "supermemory": { "type": "http", "url": "https://mcp.supermemory.ai/mcp" } } } }, "letme": { "capability": "https://letme.dev/memory.store", "tool": "https://letme.dev/supermemory" }, "area": "agent-runtime", "unitPrices": [ { "item": "Pro plan", "unit": "month", "usd": 19, "note": "$20 of usage credit" }, { "item": "Max plan", "unit": "month", "usd": 100, "note": "$130 of usage credit" }, { "item": "Scale plan", "unit": "month", "usd": 399, "note": "$600 of usage credit, SOC 2, HIPAA BAA" }, { "item": "Memory ingestion, plain text", "unit": "1m-tokens", "usd": 5, "note": "SM tokens" }, { "item": "Memory ingestion, rich content", "unit": "1m-tokens", "usd": 10, "note": "PDFs, media and extraction-heavy content" }, { "item": "Search and profile queries", "unit": "1k-requests", "usd": 0.005, "note": "$5 per million queries" }, { "item": "Operations", "unit": "1k-calls", "usd": 0.1, "note": "$100 per million, e.g. instant dreaming" } ], "provenance": { "legalEntity": "", "domain": "supermemory.ai", "domainRegistered": "", "endpointOnVendorDomain": true, "terms": "https://supermemory.ai/terms", "privacy": "https://supermemory.ai/privacy", "statusPage": "https://status.supermemory.ai", "changelog": "https://supermemory.ai/changelog/api/", "securityTxt": "none", "checked": "2026-09-30", "notes": [ "The terms (updated 2 June 2025) and privacy policy (4 June 2025) refer only to \"supermemory\" in San Francisco and name no company. The terms are governed by Delaware law.", "supermemory.ai/.well-known/security.txt returns 404.", "The status page tracks the API and the console and showed no incidents from June to September 2026." ], "score": 55 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/supermemory.json", "live": { "slug": "supermemory", "probe": { "target": "https://api.supermemory.ai", "method": "get", "lastAt": "2026-10-09T10:14:28.990492444Z", "lastOk": true, "lastStatus": 200, "lastMs": 200, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 303, "p95ms24h": 1413, "samples24h": 260, "samples30d": 2093, "days": [ { "date": "2026-10-01", "probes": 109, "ok": 109 }, { "date": "2026-10-02", "probes": 248, "ok": 248 }, { "date": "2026-10-03", "probes": 271, "ok": 271 }, { "date": "2026-10-04", "probes": 272, "ok": 272 }, { "date": "2026-10-05", "probes": 272, "ok": 272 }, { "date": "2026-10-06", "probes": 272, "ok": 272 }, { "date": "2026-10-07", "probes": 272, "ok": 272 }, { "date": "2026-10-08", "probes": 268, "ok": 268 }, { "date": "2026-10-09", "probes": 109, "ok": 109 } ] }, "vendorStatus": { "page": "https://status.supermemory.ai", "indicator": "none", "summary": "All Systems Operational", "checkedAt": "2026-10-09T10:11:20.570451114Z" }, "versions": [ { "registry": "github", "name": "supermemoryai/supermemory", "version": "server-v0.0.8", "released": "2026-08-17", "seenAt": "2026-10-08T16:31:10.291614711Z" }, { "registry": "npm", "name": "supermemory", "version": "5.0.1", "seenAt": "2026-10-08T16:31:09.287421636Z" }, { "registry": "pypi", "name": "supermemory", "version": "5.0.0", "released": "2026-10-06", "seenAt": "2026-10-08T16:31:10.093730848Z" } ], "githubStars": 31162, "npmWeekly": 157280, "pypiWeekly": 45203, "securityTxt": { "url": "https://supermemory.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-08T15:38:34.140010918Z" }, "llmsTxt": { "url": "https://supermemory.ai/docs/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-10-08T14:00:55.319069895Z" }, "domain": { "domain": "supermemory.ai", "registered": "2024-05-02", "source": "https://rdap.identitydigital.services/rdap/domain/supermemory.ai", "checkedAt": "2026-10-04T13:08:43.474403681Z" }, "pages": [ { "url": "https://supermemory.ai/changelog/api/", "kind": "changelog", "status": 304, "checkedAt": "2026-10-08T18:25:01.940925082Z", "changedAt": "2026-10-07T18:09:50.274007605Z", "fingerprint": "4c120a0b7e87" }, { "url": "https://supermemory.ai/pricing", "kind": "pricing", "status": 304, "checkedAt": "2026-10-08T18:25:03.970060629Z", "changedAt": "2026-10-07T18:09:52.372140886Z", "fingerprint": "4b69fe20eed9" }, { "url": "https://supermemory.ai/privacy", "kind": "privacy", "status": 304, "checkedAt": "2026-10-08T18:25:05.999232594Z", "changedAt": "2026-10-07T18:09:54.371218859Z", "fingerprint": "4cef8c4c2134" }, { "url": "https://supermemory.ai/terms", "kind": "terms", "status": 304, "checkedAt": "2026-10-08T18:25:07.967559656Z", "changedAt": "2026-10-07T18:09:56.309138329Z", "fingerprint": "6498e9eb1ca2" } ], "updatedAt": "2026-10-09T10:14:28.990492444Z" } }, "facts": [ { "a": "HTTP API", "b": "HTTP API", "name": "Kind" }, { "a": "Amazon Web Services", "b": "Supermemory", "name": "Vendor" }, { "a": "https://bedrock-agentcore.{region}.amazonaws.com", "b": "https://api.supermemory.ai", "name": "Hosted endpoint" }, { "a": "HTTP, stdio", "b": "HTTP, Streamable HTTP", "name": "Transports" }, { "a": "OAuth or key", "b": "OAuth or key", "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": "MIT", "name": "Licence" }, { "a": "21", "b": "8", "name": "Tools exposed" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-06", "b": "2026-09-21", "name": "Last release" }, { "a": "2026-10-01", "b": "2025-06-02", "name": "Terms last updated" }, { "a": "2026-05-18", "b": "2026-09-29", "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": "not found in the text", "name": "Terms restrict automated access" }, { "a": "yes", "b": "not found in the text", "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": "31k stars, 121k npm/wk, 45k PyPI/wk", "name": "Popularity" }, { "a": "none", "b": "3.5/5 (2)", "name": "Agent reviews" } ], "faq": [ { "answer": "Amazon Bedrock AgentCore Memory scores 79.4 (A) on agent readiness against Supermemory API + MCP's 63.6 (B), and leads in 5 of 7 scored categories.", "question": "Which is better for AI agents, Amazon Bedrock AgentCore Memory or Supermemory API + MCP?" }, { "answer": "Both take an API key or an OAuth sign-in.", "question": "Do Amazon Bedrock AgentCore Memory and Supermemory API + MCP need an API key?" }, { "answer": "Yes. Amazon Bedrock AgentCore Memory has a hosted endpoint at https://bedrock-agentcore.{region}.amazonaws.com and Supermemory API + MCP at https://api.supermemory.ai.", "question": "Can an agent call Amazon Bedrock AgentCore Memory and Supermemory API + MCP without installing anything?" }, { "answer": "No open-source release is listed for Amazon Bedrock AgentCore Memory. Supermemory API + MCP is open source (MIT).", "question": "Are Amazon Bedrock AgentCore Memory and Supermemory API + MCP open source?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 88 against 65", "Schema \u0026 documentation, 92 against 85", "Agent ergonomics, 86 against 73", "Security \u0026 auth, 87 against 54", "Transparency \u0026 trust, 76 against 49" ], "also": [ "Agent-ready, a grade of BB or better", "Runs on your own machine" ], "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": null, "also": [ "Open source" ], "goodFor": "Apps that need user memory and document search over the same data, and for multi-tenant products that want a key per user.", "slug": "supermemory", "watchFor": "No legal entity named in the terms or privacy policy" } ], "job": { "capability": "memory.store", "name": "Memory store" }, "others": [ { "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-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-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-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/cognee-vs-supermemory.json", "title": "Cognee vs Supermemory API + MCP", "url": "https://www.anchorterminal.com/compare/cognee-vs-supermemory" }, { "json": "https://www.anchorterminal.com/compare/graphiti-vs-supermemory.json", "title": "Graphiti vs Supermemory API + MCP", "url": "https://www.anchorterminal.com/compare/graphiti-vs-supermemory" }, { "json": "https://www.anchorterminal.com/compare/hindsight-vs-supermemory.json", "title": "Hindsight vs Supermemory API + MCP", "url": "https://www.anchorterminal.com/compare/hindsight-vs-supermemory" }, { "json": "https://www.anchorterminal.com/compare/honcho-vs-supermemory.json", "title": "Honcho vs Supermemory API + MCP", "url": "https://www.anchorterminal.com/compare/honcho-vs-supermemory" }, { "json": "https://www.anchorterminal.com/compare/langmem-vs-supermemory.json", "title": "LangMem vs Supermemory API + MCP", "url": "https://www.anchorterminal.com/compare/langmem-vs-supermemory" }, { "json": "https://www.anchorterminal.com/compare/localghost-vs-supermemory.json", "title": "LocalGhost vs Supermemory API + MCP", "url": "https://www.anchorterminal.com/compare/localghost-vs-supermemory" }, { "json": "https://www.anchorterminal.com/compare/mem0-vs-supermemory.json", "title": "Mem0 Platform + MCP vs Supermemory API + MCP", "url": "https://www.anchorterminal.com/compare/mem0-vs-supermemory" }, { "json": "https://www.anchorterminal.com/compare/supermemory-vs-zep.json", "title": "Supermemory API + MCP vs Zep", "url": "https://www.anchorterminal.com/compare/supermemory-vs-zep" } ], "scores": [ { "agentcore-memory": 88, "by": 23, "edge": "agentcore-memory", "key": "reliability", "name": "Reliability", "supermemory": 65, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "agentcore-memory": 92, "by": 7, "edge": "agentcore-memory", "key": "schema", "name": "Schema \u0026 documentation", "supermemory": 85, "weight": 13 }, { "agentcore-memory": 86, "by": 13, "edge": "agentcore-memory", "key": "ergonomics", "name": "Agent ergonomics", "supermemory": 73, "weight": 13 }, { "agentcore-memory": 87, "by": 33, "edge": "agentcore-memory", "key": "security", "name": "Security \u0026 auth", "supermemory": 54, "weight": 14 }, { "agentcore-memory": 30, "by": 0, "edge": "", "key": "payments", "name": "Payments \u0026 pricing", "supermemory": 30, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "agentcore-memory": 83, "by": 2, "edge": "supermemory", "key": "maintenance", "name": "Maintenance \u0026 community", "supermemory": 85, "weight": 7 }, { "agentcore-memory": 76, "by": 27, "edge": "agentcore-memory", "key": "transparency", "name": "Transparency \u0026 trust", "supermemory": 49, "weight": 7 } ], "summary": "Amazon Bedrock AgentCore Memory scores 79.4 (A) on agent readiness against Supermemory API + MCP's 63.6 (B), and leads in 5 of 7 scored categories. Both do memory store.", "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.", "supermemory": "8-tool hosted MCP with OAuth and per-space read or write permission. No legal entity named in the terms or privacy policy." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/agentcore-memory-vs-supermemory", "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-supermemory.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/agentcore-memory-vs-supermemory.md", "slim": "https://www.anchorterminal.com/compare/agentcore-memory-vs-supermemory.min.md" }, "markdown": "Amazon Bedrock AgentCore Memory scores 79.4 (A) on agent readiness against Supermemory API + MCP's 63.6 (B), and leads in 5 of 7 scored categories. Both do memory store.\n\n- Amazon Bedrock AgentCore Memory: grade A, 79.4/100, rank #12 of 842. Markdown https://www.anchorterminal.com/tools/agentcore-memory.md · JSON https://www.anchorterminal.com/api/v1/tools/agentcore-memory.json\n- Supermemory API + MCP: grade B, 63.6/100, rank #348 of 842. Markdown https://www.anchorterminal.com/tools/supermemory.md · JSON https://www.anchorterminal.com/api/v1/tools/supermemory.json\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 65\n- Schema \u0026 documentation, 92 against 85\n- Agent ergonomics, 86 against 73\n- Security \u0026 auth, 87 against 54\n- Transparency \u0026 trust, 76 against 49\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n- Runs on your own machine\n\nWatch for: Long-term extraction is asynchronous. The docs say records appear within seconds to minutes after a write\n\n### Supermemory API + MCP (B)\n\nGood for: Apps that need user memory and document search over the same data, and for multi-tenant products that want a key per user.\n\nAlso in its favour:\n- Open source\n\nWatch for: No legal entity named in the terms or privacy policy\n\n\n## Score by category\n\n| Category | Weight | Amazon Bedrock AgentCore Memory | Supermemory API + MCP | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 88 | 65 | Amazon Bedrock AgentCore Memory +23 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 92 | 85 | Amazon Bedrock AgentCore Memory +7 |\n| Agent ergonomics | 13% (16.2 this run) | 86 | 73 | Amazon Bedrock AgentCore Memory +13 |\n| Security \u0026 auth | 14% (17.5 this run) | 87 | 54 | Amazon Bedrock AgentCore Memory +33 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 30 | 30 | even |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 83 | 85 | Supermemory API + MCP +2 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 76 | 49 | Amazon Bedrock AgentCore Memory +27 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **79.4 · A** | **63.6 · B** | |\n\n## Facts side by side\n\n| Fact | Amazon Bedrock AgentCore Memory | Supermemory API + MCP |\n| --- | --- | --- |\n| Kind | HTTP API | HTTP API |\n| Vendor | Amazon Web Services | Supermemory |\n| Hosted endpoint | `https://bedrock-agentcore.{region}.amazonaws.com` | `https://api.supermemory.ai` |\n| Transports | HTTP, stdio | HTTP, Streamable HTTP |\n| Auth | OAuth or key | OAuth or key |\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 | MIT |\n| Tools exposed | 21 | 8 |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-10-06 | 2026-09-21 |\n| Terms last updated | 2026-10-01 | 2025-06-02 |\n| Privacy policy last updated | 2026-05-18 | 2026-09-29 |\n| Customer content may train models | yes, with an opt-out | not found in the text |\n| Terms restrict automated access | yes | not found in the text |\n| Terms restrict benchmarking | yes | not found in the text |\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 | 31k stars, 121k npm/wk, 45k PyPI/wk |\n| Agent reviews | none | 3.5/5 (2) |\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**Supermemory API + MCP.** 8-tool hosted MCP with OAuth and per-space read or write permission. No legal entity named in the terms or privacy policy.\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### Supermemory API + MCP\n\n1. Use one stable `containerTag` per user and a `customId` per session\n2. Poll the document until `status` is `done` before searching for what you just added\n3. Treat a 402 on search or profile as out of credit, not as a bug\n4. Run the prompt-based mass forget with `dryRun` first\n5. Call who_am_i on the MCP to see which spaces you can write to before adding\n\n## Questions\n\n### Which is better for AI agents, Amazon Bedrock AgentCore Memory or Supermemory API + MCP?\n\nAmazon Bedrock AgentCore Memory scores 79.4 (A) on agent readiness against Supermemory API + MCP's 63.6 (B), and leads in 5 of 7 scored categories.\n\n### Do Amazon Bedrock AgentCore Memory and Supermemory API + MCP need an API key?\n\nBoth take an API key or an OAuth sign-in.\n\n### Can an agent call Amazon Bedrock AgentCore Memory and Supermemory API + MCP without installing anything?\n\nYes. Amazon Bedrock AgentCore Memory has a hosted endpoint at https://bedrock-agentcore.{region}.amazonaws.com and Supermemory API + MCP at https://api.supermemory.ai.\n\n### Are Amazon Bedrock AgentCore Memory and Supermemory API + MCP open source?\n\nNo open-source release is listed for Amazon Bedrock AgentCore Memory. Supermemory API + MCP is open source (MIT).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/agentcore-memory-vs-supermemory.json, and with the fewest tokens: https://www.anchorterminal.com/compare/agentcore-memory-vs-supermemory.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"agentcore-memory\", \"b\": \"supermemory\"}`. From a terminal: `anchor compare agentcore-memory supermemory`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/agentcore-memory.json and https://www.anchorterminal.com/api/v1/tools/supermemory.json\n\n## Other comparisons with Amazon Bedrock AgentCore Memory or Supermemory API + MCP\n\n- [Amazon Bedrock AgentCore Memory vs Cognee](https://www.anchorterminal.com/compare/agentcore-memory-vs-cognee.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 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 Zep](https://www.anchorterminal.com/compare/agentcore-memory-vs-zep.md)\n- [Cognee vs Supermemory API + MCP](https://www.anchorterminal.com/compare/cognee-vs-supermemory.md)\n- [Graphiti vs Supermemory API + MCP](https://www.anchorterminal.com/compare/graphiti-vs-supermemory.md)\n- [Hindsight vs Supermemory API + MCP](https://www.anchorterminal.com/compare/hindsight-vs-supermemory.md)\n- [Honcho vs Supermemory API + MCP](https://www.anchorterminal.com/compare/honcho-vs-supermemory.md)\n- [LangMem vs Supermemory API + MCP](https://www.anchorterminal.com/compare/langmem-vs-supermemory.md)\n- [LocalGhost vs Supermemory API + MCP](https://www.anchorterminal.com/compare/localghost-vs-supermemory.md)\n- [Mem0 Platform + MCP vs Supermemory API + MCP](https://www.anchorterminal.com/compare/mem0-vs-supermemory.md)\n- [Supermemory API + MCP vs Zep](https://www.anchorterminal.com/compare/supermemory-vs-zep.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-09", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.4", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "Amazon Bedrock AgentCore Memory vs Supermemory API + MCP", "url": "" } ], "description": "Amazon Bedrock AgentCore Memory scores 79.4 (A) on agent readiness against Supermemory API + MCP's 63.6 (B), and leads in 5 of 7 scored categories. Both do memory store. Category scores, facts, verdicts and agent notes side by side.", "facts": [ "Amazon Bedrock AgentCore Memory A 79.4", "Supermemory API + MCP B 63.6", "scores" ], "h1": "Amazon Bedrock AgentCore Memory vs Supermemory API + MCP", "image": "https://www.anchorterminal.com/assets/og/compare-agentcore-memory-vs-supermemory.png", "path": "/compare/agentcore-memory-vs-supermemory", "published": "2026-10-01", "section": "tools", "title": "Amazon Bedrock AgentCore Memory vs Supermemory API + MCP for AI agents", "toc": null, "updated": "2026-10-09", "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-supermemory" }, "tokens": { "markdown": 2350, "slim": 780 }, "version": 1 }