{ "data": { "a": { "slug": "langmem", "name": "LangMem", "vendor": "LangChain", "vendorUrl": "https://www.langchain.com", "kind": "sdk", "category": "agent-memory", "summary": "LangMem is LangChain's open-source Python library for long-term agent memory. It extracts facts from conversations with an LLM, stores and searches them in a LangGraph store the owner runs, and includes two memory tools, message summarisation and prompt optimisation.", "url": "https://www.anchorterminal.com/tools/langmem", "markdownUrl": "https://www.anchorterminal.com/tools/langmem.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/langmem.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/langmem.json", "repo": "https://github.com/langchain-ai/langmem", "license": "MIT", "transports": [], "packages": [ { "registry": "pypi", "name": "langmem" } ], "auth": "none", "authNotes": "The library has no account or key of its own. It runs in the owner's process and needs a key for the chosen LLM provider (the README uses `ANTHROPIC_API_KEY`) and, for semantic search, an embedding provider. Access to memories is whatever the owner's LangGraph store and namespace settings allow.", "pricing": "free", "pricingNotes": "Free under the MIT licence, with nothing to buy and no signup. The owner pays for the LLM calls that extract memories, the embedding calls behind search, and the database behind the store (https://github.com/langchain-ai/langmem).", "priceSummary": "Free · OSS", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs or the source (checked 2026-10-08).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 1698, "npmWeekly": null, "pypiWeekly": 214379, "asOf": "2026-10-08" }, "docsUrl": "https://langchain-ai.github.io/langmem/", "capabilities": [ "memory.store", "memory.search", "memory.user", "memory.delete" ], "tags": [ "sdk", "open-source", "self-hosted", "local", "python", "free", "langgraph", "pre-1.0" ], "lastRelease": "2025-10-27", "graded": true, "anchor": { "graded": true, "score": 47.9, "grade": "D", "agentReady": false, "rank": 734, "ranked": true, "rankOf": 842, "categoryRank": 9, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 66, "maintenance": 15, "payments": 60, "reliability": 32, "schema": 55, "security": 45, "transparency": 59 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-08" }, "negative": 0, "verdict": "Two compact, typed memory tools and a background extraction manager work with any LangGraph store, under the MIT licence with nothing to buy. The newest PyPI release, 0.0.30, dates from 27 October 2025. The repository has no changelog, tags or test workflow, and 23 of 54 open issues have no reply.", "bestFor": "Teams already on LangGraph that want memory tools and background extraction over a store they run.", "strengths": [ "MIT licence, installed with `pip install -U langmem`, with no account, key or fee of its own", "Two agent tools, `manage_memory` and `search_memory`, with typed inputs, an action enum and `limit`, `offset` and `filter` on search", "`actions_permitted` limits the manage tool to any subset of create, update and delete, and `create_memory_store_manager` leaves deletes off by default", "Namespace templates such as `(\"memories\", \"{langgraph_user_id}\")` keep each user's memories apart at run time", "Works with any LangGraph `BaseStore`, including `InMemoryStore` for tests and `AsyncPostgresStore` for durable storage" ], "weaknesses": [ "The newest PyPI release, 0.0.30, is from 27 October 2025, and every commit to `src` on main is older than that", "No changelog, GitHub releases or tags, and versions are still 0.0.x", "The repository's two workflows deploy docs and publish to PyPI. Neither runs the tests", "54 open issues, 23 with no comment, and 19 open pull requests, the oldest from June 2025", "No guidance on memory poisoning or prompt injection found, and two open issues asking for it (May 2026) have no reply" ], "agentNotes": [ "Pass a store with an embedding index (`index={\"dims\": 1536, \"embed\": \"openai:text-embedding-3-small\"}`), or `search_memory` cannot rank by meaning", "Use a database-backed store such as `AsyncPostgresStore` for anything that must survive a restart. `InMemoryStore` loses everything", "Put a per-user placeholder in the namespace and set it in `config[\"configurable\"]` on every call, or users share one memory space", "Send the memory `id` with `update` and `delete`, and never with `create`. A retried `create` writes a duplicate under a new UUID", "Run on Python 3.11 or later. `src/langmem/knowledge/extraction.py` uses `typing.NotRequired`, which Python 3.10 lacks" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "D", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 47.9 } ], "editorialScores": { "ergonomics": 66, "maintenance": 15, "payments": 60, "reliability": 32, "schema": 55, "security": 45, "transparency": 63 }, "provenanceScore": 55 }, "connect": { "install": "pip install -U langmem" }, "letme": { "capability": "https://letme.dev/memory.store", "tool": "https://letme.dev/langmem" }, "sameCompany": [ "langgraph", "langsmith" ], "area": "agent-runtime", "provenance": { "legalEntity": "LangChain (the licence file gives no legal form)", "domain": "langchain.com", "domainRegistered": "2019-12-03", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-10-08", "notes": [ "A library the owner runs, with no hosted endpoint. The code is on github.com under the langchain-ai organisation and the docs are on langchain-ai.github.io/langmem.", "The LICENSE file reads Copyright (c) 2025 LangChain. PyPI metadata names no author.", "No terms or privacy document governs the library, so both fields are left out. The MIT licence is the only agreement.", "No changelog file, GitHub releases or tags exist in the repository. PyPI's release history is the only record of versions.", "www.langchain.com/.well-known/security.txt returns 404. The organisation's SECURITY.md points to two Intigriti disclosure programmes.", "RDAP for langchain.com gives a registration date of 2019-12-03." ], "score": 55 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/langmem.json" }, "answer": "Mem0 Platform + MCP scores 56.1 (C) on agent readiness against LangMem's 47.9 (D), and leads in 3 of 7 scored categories. LangMem leads on payments \u0026 pricing.", "b": { "slug": "mem0", "name": "Mem0 Platform + MCP", "vendor": "Mem0", "vendorUrl": "https://mem0.ai", "kind": "http-api", "category": "agent-memory", "summary": "Hosted memory layer that extracts facts from conversations and returns the relevant ones for a user, agent or run on later turns.", "url": "https://www.anchorterminal.com/tools/mem0", "markdownUrl": "https://www.anchorterminal.com/tools/mem0.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/mem0.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/mem0.json", "repo": "https://github.com/mem0ai/mem0", "license": "Apache-2.0", "transports": [ "http", "streamable-http" ], "remoteUrl": "https://api.mem0.ai", "packages": [ { "registry": "pypi", "name": "mem0ai" }, { "registry": "npm", "name": "mem0ai" } ], "auth": "api-key", "authNotes": "API key in the `Authorization: Token \u003ckey\u003e` header on the REST API, not Bearer. The hosted MCP at mcp.mem0.ai/mcp signs in through the browser by default, and headless clients pass the API key as a Bearer token. `mem0 init --agent` creates an unclaimed Free account with no email, limited to 5 sign-ups a day per IP address.", "pricing": "freemium", "pricingNotes": "Hobby is free with 10,000 add requests and 1,000 retrieval requests a month and 1 project. Starter is $19 a month (50,000 adds, 5,000 retrievals). Pro is $249 a month (500,000 adds, 50,000 retrievals, unlimited projects, graph memory, advanced analytics and Dream memory consolidation). Enterprise is custom, with on-prem deployment, audit logs and SSO. The page lists no overage prices or yearly discount (https://mem0.ai/pricing). The free tier needs no card (https://docs.mem0.ai/platform/platform-vs-oss).", "priceSummary": "$19 / mo", "where": "hosted", "x402": { "level": "no", "endpoints": [] }, "toolCount": 11, "popularity": { "githubStars": 65900, "npmWeekly": 167841, "pypiWeekly": 501642, "asOf": "2026-09-30" }, "docsUrl": "https://docs.mem0.ai", "llmsTxt": "https://mem0.ai/llms.txt", "openapi": "https://docs.mem0.ai/openapi.json", "registryName": "io.github.mem0ai/mem0", "capabilities": [ "memory.store", "memory.search", "memory.graph", "memory.user", "memory.delete" ], "tags": [ "hosted", "freemium", "free-tier", "no-card", "mcp", "llms-txt", "openapi", "python", "typescript", "open-source", "self-hosted", "enterprise" ], "lastRelease": "2026-09-25", "graded": true, "anchor": { "graded": true, "score": 56.1, "grade": "C", "agentReady": false, "rank": 575, "ranked": true, "rankOf": 842, "categoryRank": 5, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 63, "maintenance": 85, "payments": 50, "reliability": 30, "schema": 80, "security": 45, "transparency": 60 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-01" }, "negative": 0, "verdict": "An agent can create its own Free account with `mem0 init --agent`, no email and no card. Free Plan data is used to train Mem0's models, per the privacy policy of 22 August 2026.", "bestFor": "Chat products that want per-user facts back with one search call and little setup.", "strengths": [ "An agent can create its own Free account with `mem0 init --agent`, no email and no card", "Hosted MCP server with 11 tools, listed in the official MCP registry as io.github.mem0ai/mem0", "Public OpenAPI spec, llms.txt and Python and TypeScript SDKs, both released on 2026-09-25", "Apache-2.0 library that runs the same extraction on your own servers" ], "weaknesses": [ "Free Plan data is used to train Mem0's models, per the privacy policy of 22 August 2026", "No published rate limits or 429 handling, and only 400 and 404 documented as errors", "Retrieval caps are low below Pro, 1,000 a month free and 5,000 on Starter", "delete_all_memories and delete_entities are in the default MCP tool list with no read-only mode", "SOC 2 Type I, not Type II, and no security.txt" ], "agentNotes": [ "Send the REST key as `Authorization: Token \u003ckey\u003e`, and the MCP key as Bearer", "Don't search for a memory straight after adding it. Adds are queued, so poll get_event_status with the returned event ID", "Scope every add and search with `user_id` (or agent and run IDs) so memories don't mix between users", "Pass a filter on every bulk delete, since delete_all_memories wipes whatever the scope matches", "On Hobby and Starter, count retrievals rather than adds. The retrieval quota is a tenth the size" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 2, "avgRating": 2.5, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "C", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 56.1 } ], "editorialScores": { "ergonomics": 63, "maintenance": 85, "payments": 50, "reliability": 30, "schema": 80, "security": 45, "transparency": 56 }, "provenanceScore": 64 }, "connect": { "install": "pip install mem0ai # or: npm install mem0ai", "http": "curl -X POST https://api.mem0.ai/v1/memories/ -H \"Authorization: Token $MEM0_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\"messages\":[{\"role\":\"user\",\"content\":\"I am vegetarian and allergic to nuts.\"}],\"user_id\":\"alex\"}'", "claudeCode": "claude mcp add --transport http mem0 https://mcp.mem0.ai/mcp --header \"Authorization: Bearer $MEM0_API_KEY\"", "config": { "mcpServers": { "mem0": { "headers": { "Authorization": "Bearer ${MEM0_API_KEY}" }, "type": "http", "url": "https://mcp.mem0.ai/mcp" } } } }, "letme": { "capability": "https://letme.dev/memory.store", "tool": "https://letme.dev/mem0" }, "area": "agent-runtime", "unitPrices": [ { "item": "Starter plan", "unit": "month", "usd": 19, "note": "50,000 adds and 5,000 retrievals a month" }, { "item": "Pro plan", "unit": "month", "usd": 249, "note": "500,000 adds and 50,000 retrievals a month, graph memory" } ], "provenance": { "legalEntity": "Embedchain, Inc. (DBA Mem0)", "domain": "mem0.ai", "domainRegistered": "", "endpointOnVendorDomain": true, "terms": "https://mem0.ai/terms", "privacy": "https://mem0.ai/privacy-policy", "statusPage": "https://status.mem0.ai", "changelog": "https://docs.mem0.ai/changelog/platform", "securityTxt": "none", "checked": "2026-09-30", "notes": [ "The privacy policy, last updated 22 August 2026, names Embedchain, Inc. doing business as Mem0, and lists OpenAI and Anthropic among the AI providers that process data.", "mem0.ai/.well-known/security.txt returns 404." ], "score": 64 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/mem0.json", "live": { "slug": "mem0", "probe": { "target": "https://api.mem0.ai", "method": "get", "lastAt": "2026-10-09T11:29:05.707032069Z", "lastOk": true, "lastStatus": 200, "lastMs": 484, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 452, "p95ms24h": 488, "samples24h": 259, "samples30d": 2106, "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": 122, "ok": 122 } ] }, "vendorStatus": { "page": "https://status.mem0.ai", "indicator": "unknown", "summary": "no machine-readable status found", "checkedAt": "2026-10-09T07:58:09.169136094Z" }, "versions": [ { "registry": "github", "name": "mem0ai/mem0", "version": "ts-v3.3.1", "released": "2026-09-25", "seenAt": "2026-10-08T16:20:15.661271479Z" }, { "registry": "mcp-registry", "name": "io.github.mem0ai/mem0", "version": "1.0.0", "seenAt": "2026-10-09T02:57:46.004536428Z" }, { "registry": "npm", "name": "mem0ai", "version": "3.3.1", "seenAt": "2026-10-08T16:20:13.401292253Z" }, { "registry": "pypi", "name": "mem0ai", "version": "2.2.1", "released": "2026-09-25", "seenAt": "2026-10-08T16:20:13.245027457Z" } ], "githubStars": 66824, "npmWeekly": 196491, "pypiWeekly": 472618, "securityTxt": { "url": "https://mem0.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-08T15:38:41.470874617Z" }, "llmsTxt": { "url": "https://mem0.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-10-08T14:00:36.214574018Z" }, "domain": { "domain": "mem0.ai", "registered": "2024-05-15", "source": "https://rdap.identitydigital.services/rdap/domain/mem0.ai", "checkedAt": "2026-10-04T13:05:24.712383123Z" }, "pages": [ { "url": "https://docs.mem0.ai/changelog/platform", "kind": "changelog", "status": 200, "checkedAt": "2026-10-08T18:19:05.55562819Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "260709ea3b0d" }, { "url": "https://mem0.ai/pricing", "kind": "pricing", "status": 200, "checkedAt": "2026-10-08T18:21:56.275364447Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "a0e74db1e2b1" }, { "url": "https://mem0.ai/privacy-policy", "kind": "privacy", "status": 200, "checkedAt": "2026-10-08T18:21:58.445908698Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "6ca47106ef6c" }, { "url": "https://mem0.ai/terms", "kind": "terms", "status": 200, "checkedAt": "2026-10-08T18:22:00.611372987Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "8cbc548b1c9a" } ], "updatedAt": "2026-10-09T11:29:05.707032069Z" } }, "facts": [ { "a": "SDK + MCP", "b": "HTTP API", "name": "Kind" }, { "a": "LangChain", "b": "Mem0", "name": "Vendor" }, { "a": "no (local only)", "b": "https://api.mem0.ai", "name": "Hosted endpoint" }, { "a": "", "b": "HTTP, Streamable HTTP", "name": "Transports" }, { "a": "None", "b": "API key", "name": "Auth" }, { "a": "Free", "b": "Freemium", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "MIT", "b": "Apache-2.0", "name": "Licence" }, { "a": "none", "b": "11", "name": "Tools exposed" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "yes", "name": "llms.txt" }, { "a": "not listed", "b": "io.github.mem0ai/mem0", "name": "MCP registry" }, { "a": "2025-10-27", "b": "2026-09-25", "name": "Last release" }, { "a": "no document linked", "b": "no date given", "name": "Terms last updated" }, { "a": "no document linked", "b": "no date given", "name": "Privacy policy last updated" }, { "a": "", "b": "yes", "name": "Customer content may train models" }, { "a": "", "b": "yes", "name": "Terms restrict automated access" }, { "a": "", "b": "yes", "name": "Terms restrict benchmarking" }, { "a": "", "b": "not found in the text", "name": "Terms or service can change without notice" }, { "a": "", "b": "yes", "name": "Arbitration or class-action waiver" }, { "a": "1.7k stars, 214k PyPI/wk", "b": "66k stars, 168k npm/wk, 502k PyPI/wk", "name": "Popularity" }, { "a": "none", "b": "2.5/5 (2)", "name": "Agent reviews" } ], "faq": [ { "answer": "Mem0 Platform + MCP scores 56.1 (C) on agent readiness against LangMem's 47.9 (D), and leads in 3 of 7 scored categories. LangMem leads on payments \u0026 pricing.", "question": "Which is better for AI agents, LangMem or Mem0 Platform + MCP?" }, { "answer": "No hosted endpoint is listed for LangMem. Mem0 Platform + MCP has a hosted endpoint at https://api.mem0.ai.", "question": "Can an agent call LangMem and Mem0 Platform + MCP without installing anything?" }, { "answer": "Yes. LangMem is open source (MIT). Mem0 Platform + MCP is open source (Apache-2.0).", "question": "Are LangMem and Mem0 Platform + MCP open source?" } ], "goodFor": [ { "aheadOn": [ "Payments \u0026 pricing, 60 against 50" ], "also": [ "No key needed to call it" ], "goodFor": "Teams already on LangGraph that want memory tools and background extraction over a store they run.", "slug": "langmem", "watchFor": "The newest PyPI release, 0.0.30, is from 27 October 2025, and every commit to `src` on main is older than that" }, { "aheadOn": [ "Schema \u0026 documentation, 80 against 55", "Maintenance \u0026 community, 85 against 15" ], "also": [ "A hosted endpoint, with nothing to install", "Free to start without a card" ], "goodFor": "Chat products that want per-user facts back with one search call and little setup.", "slug": "mem0", "watchFor": "Free Plan data is used to train Mem0's models, per the privacy policy of 22 August 2026" } ], "job": { "capability": "memory.store", "name": "Memory store" }, "others": [ { "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-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/cognee-vs-langmem.json", "title": "Cognee vs LangMem", "url": "https://www.anchorterminal.com/compare/cognee-vs-langmem" }, { "json": "https://www.anchorterminal.com/compare/cognee-vs-mem0.json", "title": "Cognee vs Mem0 Platform + MCP", "url": "https://www.anchorterminal.com/compare/cognee-vs-mem0" }, { "json": "https://www.anchorterminal.com/compare/graphiti-vs-langmem.json", "title": "Graphiti vs LangMem", "url": "https://www.anchorterminal.com/compare/graphiti-vs-langmem" }, { "json": "https://www.anchorterminal.com/compare/graphiti-vs-mem0.json", "title": "Graphiti vs Mem0 Platform + MCP", "url": "https://www.anchorterminal.com/compare/graphiti-vs-mem0" }, { "json": "https://www.anchorterminal.com/compare/hindsight-vs-langmem.json", "title": "Hindsight vs LangMem", "url": "https://www.anchorterminal.com/compare/hindsight-vs-langmem" }, { "json": "https://www.anchorterminal.com/compare/hindsight-vs-mem0.json", "title": "Hindsight vs Mem0 Platform + MCP", "url": "https://www.anchorterminal.com/compare/hindsight-vs-mem0" }, { "json": "https://www.anchorterminal.com/compare/honcho-vs-langmem.json", "title": "Honcho vs LangMem", "url": "https://www.anchorterminal.com/compare/honcho-vs-langmem" }, { "json": "https://www.anchorterminal.com/compare/honcho-vs-mem0.json", "title": "Honcho vs Mem0 Platform + MCP", "url": "https://www.anchorterminal.com/compare/honcho-vs-mem0" }, { "json": "https://www.anchorterminal.com/compare/langmem-vs-localghost.json", "title": "LangMem vs LocalGhost", "url": "https://www.anchorterminal.com/compare/langmem-vs-localghost" }, { "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/langmem-vs-zep.json", "title": "LangMem vs Zep", "url": "https://www.anchorterminal.com/compare/langmem-vs-zep" }, { "json": "https://www.anchorterminal.com/compare/localghost-vs-mem0.json", "title": "LocalGhost vs Mem0 Platform + MCP", "url": "https://www.anchorterminal.com/compare/localghost-vs-mem0" }, { "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/mem0-vs-zep.json", "title": "Mem0 Platform + MCP vs Zep", "url": "https://www.anchorterminal.com/compare/mem0-vs-zep" } ], "scores": [ { "by": 2, "edge": "langmem", "key": "reliability", "langmem": 32, "mem0": 30, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 25, "edge": "mem0", "key": "schema", "langmem": 55, "mem0": 80, "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 3, "edge": "langmem", "key": "ergonomics", "langmem": 66, "mem0": 63, "name": "Agent ergonomics", "weight": 13 }, { "by": 0, "edge": "", "key": "security", "langmem": 45, "mem0": 45, "name": "Security \u0026 auth", "weight": 14 }, { "by": 10, "edge": "langmem", "key": "payments", "langmem": 60, "mem0": 50, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 70, "edge": "mem0", "key": "maintenance", "langmem": 15, "mem0": 85, "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 1, "edge": "mem0", "key": "transparency", "langmem": 59, "mem0": 60, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Mem0 Platform + MCP scores 56.1 (C) on agent readiness against LangMem's 47.9 (D), and leads in 3 of 7 scored categories. LangMem leads on payments \u0026 pricing. Both do memory store.", "verdicts": { "langmem": "Two compact, typed memory tools and a background extraction manager work with any LangGraph store, under the MIT licence with nothing to buy. The newest PyPI release, 0.0.30, dates from 27 October 2025. The repository has no changelog, tags or test workflow, and 23 of 54 open issues have no reply.", "mem0": "An agent can create its own Free account with `mem0 init --agent`, no email and no card. Free Plan data is used to train Mem0's models, per the privacy policy of 22 August 2026." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/langmem-vs-mem0", "json": "https://www.anchorterminal.com/compare/langmem-vs-mem0.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/langmem-vs-mem0.md", "slim": "https://www.anchorterminal.com/compare/langmem-vs-mem0.min.md" }, "markdown": "Mem0 Platform + MCP scores 56.1 (C) on agent readiness against LangMem's 47.9 (D), and leads in 3 of 7 scored categories. LangMem leads on payments \u0026 pricing. Both do memory store.\n\n- LangMem: grade D, 47.9/100, rank #734 of 842. Markdown https://www.anchorterminal.com/tools/langmem.md · JSON https://www.anchorterminal.com/api/v1/tools/langmem.json\n- Mem0 Platform + MCP: grade C, 56.1/100, rank #575 of 842. Markdown https://www.anchorterminal.com/tools/mem0.md · JSON https://www.anchorterminal.com/api/v1/tools/mem0.json\n\n## Which one, for what\n\n### LangMem (D)\n\nGood for: Teams already on LangGraph that want memory tools and background extraction over a store they run.\n\nAhead on:\n- Payments \u0026 pricing, 60 against 50\n\nAlso in its favour:\n- No key needed to call it\n\nWatch for: The newest PyPI release, 0.0.30, is from 27 October 2025, and every commit to `src` on main is older than that\n\n### Mem0 Platform + MCP (C)\n\nGood for: Chat products that want per-user facts back with one search call and little setup.\n\nAhead on:\n- Schema \u0026 documentation, 80 against 55\n- Maintenance \u0026 community, 85 against 15\n\nAlso in its favour:\n- A hosted endpoint, with nothing to install\n- Free to start without a card\n\nWatch for: Free Plan data is used to train Mem0's models, per the privacy policy of 22 August 2026\n\n\n## Score by category\n\n| Category | Weight | LangMem | Mem0 Platform + MCP | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 32 | 30 | LangMem +2 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 55 | 80 | Mem0 Platform + MCP +25 |\n| Agent ergonomics | 13% (16.2 this run) | 66 | 63 | LangMem +3 |\n| Security \u0026 auth | 14% (17.5 this run) | 45 | 45 | even |\n| Payments \u0026 pricing | 10% (12.5 this run) | 60 | 50 | LangMem +10 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 15 | 85 | Mem0 Platform + MCP +70 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 59 | 60 | Mem0 Platform + MCP +1 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **47.9 · D** | **56.1 · C** | |\n\n## Facts side by side\n\n| Fact | LangMem | Mem0 Platform + MCP |\n| --- | --- | --- |\n| Kind | SDK + MCP | HTTP API |\n| Vendor | LangChain | Mem0 |\n| Hosted endpoint | no (local only) | `https://api.mem0.ai` |\n| Transports | | HTTP, Streamable HTTP |\n| Auth | None | API key |\n| Pricing | Free | Freemium |\n| x402 | no | no |\n| Licence | MIT | Apache-2.0 |\n| Tools exposed | none | 11 |\n| Read-only variant documented | no | no |\n| llms.txt | no | yes |\n| MCP registry | not listed | `io.github.mem0ai/mem0` |\n| Last release | 2025-10-27 | 2026-09-25 |\n| Terms last updated | no document linked | no date given |\n| Privacy policy last updated | no document linked | no date given |\n| Customer content may train models | | yes |\n| Terms restrict automated access | | yes |\n| Terms restrict benchmarking | | yes |\n| Terms or service can change without notice | | not found in the text |\n| Arbitration or class-action waiver | | yes |\n| Popularity | 1.7k stars, 214k PyPI/wk | 66k stars, 168k npm/wk, 502k PyPI/wk |\n| Agent reviews | none | 2.5/5 (2) |\n\n## Verdicts\n\n**LangMem.** Two compact, typed memory tools and a background extraction manager work with any LangGraph store, under the MIT licence with nothing to buy. The newest PyPI release, 0.0.30, dates from 27 October 2025. The repository has no changelog, tags or test workflow, and 23 of 54 open issues have no reply.\n\n**Mem0 Platform + MCP.** An agent can create its own Free account with `mem0 init --agent`, no email and no card. Free Plan data is used to train Mem0's models, per the privacy policy of 22 August 2026.\n\n## Before you call either\n\n### LangMem\n\n1. Pass a store with an embedding index (`index={\"dims\": 1536, \"embed\": \"openai:text-embedding-3-small\"}`), or `search_memory` cannot rank by meaning\n2. Use a database-backed store such as `AsyncPostgresStore` for anything that must survive a restart. `InMemoryStore` loses everything\n3. Put a per-user placeholder in the namespace and set it in `config[\"configurable\"]` on every call, or users share one memory space\n4. Send the memory `id` with `update` and `delete`, and never with `create`. A retried `create` writes a duplicate under a new UUID\n5. Run on Python 3.11 or later. `src/langmem/knowledge/extraction.py` uses `typing.NotRequired`, which Python 3.10 lacks\n\n### Mem0 Platform + MCP\n\n1. Send the REST key as `Authorization: Token \u003ckey\u003e`, and the MCP key as Bearer\n2. Don't search for a memory straight after adding it. Adds are queued, so poll get_event_status with the returned event ID\n3. Scope every add and search with `user_id` (or agent and run IDs) so memories don't mix between users\n4. Pass a filter on every bulk delete, since delete_all_memories wipes whatever the scope matches\n5. On Hobby and Starter, count retrievals rather than adds. The retrieval quota is a tenth the size\n\n## Questions\n\n### Which is better for AI agents, LangMem or Mem0 Platform + MCP?\n\nMem0 Platform + MCP scores 56.1 (C) on agent readiness against LangMem's 47.9 (D), and leads in 3 of 7 scored categories. LangMem leads on payments \u0026 pricing.\n\n### Can an agent call LangMem and Mem0 Platform + MCP without installing anything?\n\nNo hosted endpoint is listed for LangMem. Mem0 Platform + MCP has a hosted endpoint at https://api.mem0.ai.\n\n### Are LangMem and Mem0 Platform + MCP open source?\n\nYes. LangMem is open source (MIT). Mem0 Platform + MCP is open source (Apache-2.0).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/langmem-vs-mem0.json, and with the fewest tokens: https://www.anchorterminal.com/compare/langmem-vs-mem0.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"langmem\", \"b\": \"mem0\"}`. From a terminal: `anchor compare langmem mem0`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/langmem.json and https://www.anchorterminal.com/api/v1/tools/mem0.json\n\n## Other comparisons with LangMem or Mem0 Platform + MCP\n\n- [Amazon Bedrock AgentCore Memory vs LangMem](https://www.anchorterminal.com/compare/agentcore-memory-vs-langmem.md)\n- [Amazon Bedrock AgentCore Memory vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/agentcore-memory-vs-mem0.md)\n- [Cognee vs LangMem](https://www.anchorterminal.com/compare/cognee-vs-langmem.md)\n- [Cognee vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/cognee-vs-mem0.md)\n- [Graphiti vs LangMem](https://www.anchorterminal.com/compare/graphiti-vs-langmem.md)\n- [Graphiti vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/graphiti-vs-mem0.md)\n- [Hindsight vs LangMem](https://www.anchorterminal.com/compare/hindsight-vs-langmem.md)\n- [Hindsight vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/hindsight-vs-mem0.md)\n- [Honcho vs LangMem](https://www.anchorterminal.com/compare/honcho-vs-langmem.md)\n- [Honcho vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/honcho-vs-mem0.md)\n- [LangMem vs LocalGhost](https://www.anchorterminal.com/compare/langmem-vs-localghost.md)\n- [LangMem vs Supermemory API + MCP](https://www.anchorterminal.com/compare/langmem-vs-supermemory.md)\n- [LangMem vs Zep](https://www.anchorterminal.com/compare/langmem-vs-zep.md)\n- [LocalGhost vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/localghost-vs-mem0.md)\n- [Mem0 Platform + MCP vs Supermemory API + MCP](https://www.anchorterminal.com/compare/mem0-vs-supermemory.md)\n- [Mem0 Platform + MCP vs Zep](https://www.anchorterminal.com/compare/mem0-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": "LangMem vs Mem0 Platform + MCP", "url": "" } ], "description": "Mem0 Platform + MCP scores 56.1 (C) on agent readiness against LangMem's 47.9 (D), and leads in 3 of 7 scored categories. LangMem leads on payments \u0026 pricing. Both do memory store. Category scores, facts, verdicts and agent notes side by side.", "facts": [ "LangMem D 47.9", "Mem0 Platform + MCP C 56.1", "scores" ], "h1": "LangMem vs Mem0 Platform + MCP", "image": "https://www.anchorterminal.com/assets/og/compare-langmem-vs-mem0.png", "path": "/compare/langmem-vs-mem0", "published": "2026-10-01", "section": "tools", "title": "LangMem vs Mem0 Platform + MCP for AI agents, D 47.9 vs C 56.1", "toc": null, "updated": "2026-10-09", "url": "https://www.anchorterminal.com/compare/langmem-vs-mem0" }, "tokens": { "markdown": 2100, "slim": 680 }, "version": 1 }