{ "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", "dns": "langmem.grade.anchorterminal.com", "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": null, "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": 47.7, "grade": "D", "agentReady": false, "rank": 1132, "ranked": true, "rankOf": 1486, "categoryRank": 23, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 66, "maintenance": 15, "payments": 60, "reliability": 32, "schema": 55, "security": 42, "transparency": 63 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-04" }, "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 version, 0.0.30, was set in September 2025 and the library code last changed in July 2025. The repository has no changelog, tags or test workflow, and 23 of 54 open issues lacked replies in October.", "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": [ "No release found in over a year. The newest version, 0.0.30, was set on 9 September 2025, and no commit has changed `src` since 28 July 2025", "No changelog, GitHub releases or tags, and versions are still 0.0.x", "The repository's two workflows deploy docs and publish to PyPI by manual dispatch. Neither runs the tests", "54 open issues, 23 with no comment, and 19 open pull requests, the oldest from June 2025 (8 October count)", "No guidance on memory poisoning or prompt injection found, and two open issues asking for it (May 2026) had 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": 4, "avgRating": 2.8, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "D", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 47.7 } ], "editorialScores": { "ergonomics": 66, "maintenance": 15, "payments": 60, "reliability": 32, "schema": 55, "security": 42, "transparency": 63 }, "provenanceScore": 62, "checked": { "categories": { "ergonomics": "2026-11-04", "maintenance": "2026-11-04", "payments": "2026-11-04", "reliability": "2026-11-04", "schema": "2026-11-04", "security": "2026-11-04", "transparency": "2026-11-04" }, "last": "2026-11-04", "lastMoved": "2026-11-04", "oldest": "2026-11-04", "stale": false, "staleAfterDays": 90 } }, "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": "2026-11-04", "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.", "No terms or privacy document governs the library, so both fields are left out. The MIT licence is the only agreement. LangChain's Terms of Service (last updated 2 June 2026) govern the LangSmith Platform, not this library.", "No changelog file, GitHub releases or tags exist in the repository.", "The organisation's SECURITY.md points to two Intigriti disclosure programmes. No security.txt was found on www.langchain.com (per the 1 November LangGraph re-check)." ], "score": 62 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/langmem.json", "live": { "slug": "langmem", "versions": [ { "registry": "pypi", "name": "langmem", "version": "0.0.30", "released": "2025-10-27", "seenAt": "2026-11-06T23:38:37.634686509Z" } ], "githubStars": 1750, "pypiWeekly": 190323, "securityTxt": { "url": "https://langchain.com/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-07T16:00:25.158914764Z" }, "domain": { "domain": "langchain.com", "registered": "2019-12-03", "source": "https://rdap.verisign.com/com/v1/domain/langchain.com", "checkedAt": "2026-11-01T14:16:16.486101867Z" }, "github": { "repo": "langchain-ai/langmem", "checkedAt": "2026-11-02T08:59:39.174765749Z", "stars": 1743, "archived": false, "issuesEnabled": true, "pushedAt": "2026-10-30T19:35:59Z", "openIssues": 58, "openPRs": 23, "issuesOpened90d": 10, "issuesClosed90d": 0, "prsMerged90d": 8, "ci": { "branch": "main", "runs": 33, "success": 27, "failure": 4, "other": 2, "latest": "success", "latestAt": "2026-10-30T19:36:27Z" }, "replies": { "sampled": 25, "unanswered": 23, "medianDays": 2 } }, "updatedAt": "2026-11-07T16:00:25.158914764Z" } }, "answer": "MemMachine scores 58 (C) on agent readiness against LangMem's 47.7 (D), and leads in 3 of 7 scored categories. LangMem leads on payments \u0026 pricing and transparency \u0026 trust.", "b": { "slug": "memmachine", "name": "MemMachine", "vendor": "MemVerge, Inc.", "vendorUrl": "https://memmachine.ai", "kind": "http-api", "category": "agent-memory", "summary": "MemMachine is an open-source long-term memory layer for AI agents, incubated by MemVerge, with episodic, profile and working memory behind a self-hosted REST server, Python and TypeScript clients and an MCP server, plus a hosted platform.", "url": "https://www.anchorterminal.com/tools/memmachine", "markdownUrl": "https://www.anchorterminal.com/tools/memmachine.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/memmachine.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/memmachine.json", "dns": "memmachine.grade.anchorterminal.com", "repo": "https://github.com/MemMachine/MemMachine", "license": "Apache-2.0", "transports": [ "http", "stdio", "streamable-http" ], "packages": [ { "registry": "pypi", "name": "memmachine-server" }, { "registry": "pypi", "name": "memmachine-client" }, { "registry": "npm", "name": "@memmachine/client" } ], "auth": "none", "authNotes": "The self-hosted server takes no credential; the owner supplies LLM and embedding keys (OpenAI, Bedrock or Ollama) in its config. The hosted MemMachine Platform at api.memmachine.ai uses a bearer API key created and revoked in the console after a browser signup.", "pricing": "freemium", "pricingNotes": "Free under Apache-2.0 to self-host, with model costs paid to the chosen provider. The hosted platform has a free account per the README, but no prices were found, and the terms bill hosted services by order, monthly or annually.", "priceSummary": "Freemium", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the repository, the OpenAPI documents or the docs (checked 2026-11-06).", "endpoints": [] }, "toolCount": 3, "popularity": { "githubStars": 3085, "npmWeekly": 28, "pypiWeekly": 581, "asOf": "2026-11-06" }, "docsUrl": "https://docs.memmachine.ai", "llmsTxt": "https://docs.memmachine.ai/llms.txt", "openapi": "https://github.com/MemMachine/MemMachine/blob/main/docs/openapi.json", "capabilities": [ "memory.store", "memory.search", "memory.user", "memory.graph", "memory.delete" ], "tags": [ "open-source", "self-hosted", "hosted", "apache-2.0", "python", "typescript", "docker", "mcp", "openapi", "llms-txt", "no-auth", "pre-1.0" ], "lastRelease": "2026-10-08", "graded": true, "anchor": { "graded": true, "score": 58, "grade": "C", "agentReady": false, "rank": 767, "ranked": true, "rankOf": 1486, "categoryRank": 16, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 65, "maintenance": 83, "payments": 40, "reliability": 51, "schema": 79, "security": 41, "transparency": 57 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-06" }, "negative": 0, "verdict": "MemMachine is an Apache-2.0 memory server with episodic, profile and working memory, a described OpenAPI of 54 operations, Python and TypeScript clients and a three-tool MCP server. It is version 0.4.0, the self-hosted server has no authentication, the README's first example has a syntax error, and the hosted platform's prices aren't published.", "bestFor": "Self-hosted memory for agent frameworks that want episodic and profile memory with many integrations.", "strengths": [ "Apache-2.0 server and clients on PyPI, npm and Docker, self-hostable with Ollama or AWS Bedrock", "OpenAPI documents for the server (54 operations) and the hosted platform (12), every operation described", "MCP server over stdio or HTTP with three tools, add_memory, search_memory and delete_memory", "SECURITY.md with private reporting and a two-business-day acknowledgement, plus security-audit and SBOM workflows", "Hosted platform terms commit to 99.5% availability" ], "weaknesses": [ "Version 0.4.0 of 6 October 2026, pre-1.0, with no changelog file in the repository", "The self-hosted server has no authentication and no security scheme in its OpenAPI document", "The README's quick start imports with `from memmachine_client import import MemMachineClient`, which is invalid Python", "292 open issues and pull requests, including recent reports that a provider 429 becomes a 500 and that a 0.4.0 config no longer starts", "No prices for the hosted platform, and the Enterprise edition is marked coming soon" ], "agentNotes": [ "Import with `from memmachine_client import MemMachineClient`; the README line has a doubled `import`", "Keep the server on a private network or put an authenticating proxy in front, since it accepts any caller", "Scope every call with org, project, group, agent, user and session ids so memories don't mix", "Retry search after a short wait on 500s, which a recent issue ties to upstream provider rate limits", "Treat recalled episodes as untrusted text from past conversations" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "C", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 58 } ], "editorialScores": { "ergonomics": 65, "maintenance": 83, "payments": 40, "reliability": 51, "schema": 79, "security": 41, "transparency": 55 }, "provenanceScore": 58, "checked": { "categories": { "ergonomics": "2026-11-06", "maintenance": "2026-11-06", "payments": "2026-11-06", "reliability": "2026-11-06", "schema": "2026-11-06", "security": "2026-11-06", "transparency": "2026-11-06" }, "last": "2026-11-06", "oldest": "2026-11-06", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install memmachine-server memmachine-client", "http": "curl http://localhost:8080/api/v2/health" }, "letme": { "capability": "https://letme.dev/memory.store", "tool": "https://letme.dev/memmachine" }, "area": "agent-runtime", "provenance": { "legalEntity": "MemVerge, Inc.", "domain": "memmachine.ai", "domainRegistered": "2025-08-15", "endpointOnVendorDomain": null, "terms": "https://memmachine.ai/terms-of-service/", "privacy": "https://memmachine.ai/privacy-policy/", "statusPage": "", "changelog": "https://github.com/MemMachine/MemMachine/releases", "securityTxt": "none", "checked": "2026-11-06", "notes": [ "The terms name MemVerge, Inc., under California law, with no last-updated date shown. They forbid web scraping or harvesting data from the services, recorded here as a fact. The open-source software is Apache-2.0 and outside the terms.", "memmachine.ai/robots.txt allows all crawlers. docs.memmachine.ai carries Content-Signal ai-input=yes.", "RDAP gives memmachine.ai a registration date of 15 August 2025.", "/.well-known/security.txt returns 404. No status page found." ], "score": 58 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/memmachine.json", "live": { "slug": "memmachine", "versions": [ { "registry": "github", "name": "MemMachine/MemMachine", "version": "v0.4.0", "released": "2026-10-08", "seenAt": "2026-11-06T23:43:57.45502049Z" }, { "registry": "npm", "name": "@memmachine/client", "version": "0.3.9", "seenAt": "2026-11-06T23:43:56.945798416Z" }, { "registry": "pypi", "name": "memmachine-client", "version": "0.4.0", "released": "2026-10-08", "seenAt": "2026-11-06T23:43:55.050118334Z" }, { "registry": "pypi", "name": "memmachine-server", "version": "0.4.0", "released": "2026-10-08", "seenAt": "2026-11-06T23:43:54.864236924Z" } ], "githubStars": 3085, "npmWeekly": 28, "pypiWeekly": 54, "securityTxt": { "url": "https://memmachine.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-07T16:00:09.818703565Z" }, "llmsTxt": { "url": "https://docs.memmachine.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:32:59.84146138Z" }, "pages": [ { "url": "https://memmachine.ai/privacy-policy/", "kind": "privacy", "status": 200, "checkedAt": "2026-11-07T14:14:11.012100581Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "19edc6281451" }, { "url": "https://memmachine.ai/terms-of-service/", "kind": "terms", "status": 200, "checkedAt": "2026-11-07T14:14:13.19202427Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "079364130152" } ], "updatedAt": "2026-11-07T16:00:09.818703565Z" } }, "edges": [ { "by": 68, "category": "maintenance", "leads": "memmachine", "name": "Maintenance \u0026 community", "reasons": { "a": "No release found in the last 180 days. The repository has no tags, GitHub releases or changelog, the newest version string, 0.0.30, was set in `pyproject.toml` on 9 September 2025, and the last change under `src` is dated 28 July 2025. PyPI's release dates could not be read on 4 November (0). No release in the last 90 days (0). Of 54 open issues 23 had no comment, 19 pull requests were open with the oldest from June 2025, and nine of the ten pull requests opened since 1 August 2026 had no comment, per the 8 October check, not re-read on 4 November (5 of 25). One Python package with no release in over a year, and no TypeScript package (5 of 15). Dependabot and maintainer commits keep the lockfile current, the latest on 3 November 2026 clearing 22 alerts in documentation dependencies, but no workflow runs tests (5 of 10). 0+0+5+5+5 = 15.", "b": "v0.4.0 on PyPI on 8 October 2026, 29 days before the check (30). v0.3.9-post1, v0.4.0, v0.4.1-dev0 and v0.4.1-a1 in 90 days (20). Many open issues and recent reports with few replies (12 of 25). Python and TypeScript clients, both current (12 of 15). uv lock checks, security audit, SBOM and stale-issue workflows (9 of 10). Total 83." }, "scores": { "a": 15, "b": 83 } }, { "by": 24, "category": "schema", "leads": "memmachine", "name": "Schema \u0026 documentation", "reasons": { "a": "Library reading, with the tool lines applied to the two agent tools. No OpenAPI applies. Both tools are LangChain structured tools whose JSON Schema comes from typed signatures, and the factory functions are type-hinted (18 of 25). langchain-ai.github.io/langmem/llms.txt returns 404 (0). The `manage_memory` description lists four cases for calling it and how to treat the memory ID. `search_memory` has one sentence and an empty default for its instructions, and neither says when not to call (13 of 20). `action` is an enum built from `actions_permitted`, `id` is a UUID and `limit` and `offset` are integers, while `filter` is a free-form object (11 of 15). Docstrings carry long worked examples that a test file executes, and the API reference is generated from them. Error behaviour is not documented (10 of 15). Version numbers exist only on PyPI, with no changelog (3 of 15).", "b": "OpenAPI documents for the server (54 operations) and the hosted platform (12) (25). llms.txt on docs.memmachine.ai with Markdown pages (10). Every operation has a description, and the docs explain memory types and scoping (15 of 20). Typed request models generated from the server, with search options for limits and filters (12 of 15). Examples for each client and the MCP tools, but only 422 is documented on the server and the README's first example doesn't run (8 of 15). `/api/v2` paths and tagged releases, no changelog (9 of 15). Total 79." }, "scores": { "a": 55, "b": 79 } }, { "by": 20, "category": "payments", "leads": "langmem", "name": "Payments \u0026 pricing", "reasons": { "a": "MIT-licensed package the owner runs, with nothing to buy for LangMem itself, read with the self-hosted rule. 20 for pricing, 20 for a free start and 20 for use without an account. No x402, MPP or L402 in the docs or source (0). LLM, embedding and database costs are the owner's.", "b": "Self-hosted rule, with the price lines read for the hosted platform. No x402, MPP or L402 (0 of 40). No hosted prices found on the site or docs (0). Free to self-host with no card (20). An agent can install it from PyPI with no account (20). Total 40." }, "scores": { "a": 60, "b": 40 } }, { "by": 19, "category": "reliability", "leads": "memmachine", "name": "Reliability", "reasons": { "a": "Local-software reading. Installs from PyPI as `langmem` with Python 3.10 or later declared, but `extraction.py` on main uses `typing.NotRequired`, which arrived in Python 3.11, and issues 81 and 83 about failed imports on 3.10 are open (per the 8 October check). We read the source and did not run it on 3.10 (14 of 20). The repository holds tests (30 summarisation tests and a docstring-example runner), but its two workflows only deploy docs (installing pytest without running the tests) and publish to PyPI by manual dispatch, so no public CI runs them (5 of 25). 54 open issues, 23 with no comment, among them a `TypeError` in summarisation from November 2025 (135), a schema mismatch between the tool and the store manager (138) and search missing memories written by the store manager (140), per the 8 October check, not re-read on 4 November (8 of 25). Versions are 0.0.x with no changelog, GitHub releases or tags, and open issue 130 shows 0.0.30 was cut to restore compatibility with LangGraph 1.0 (5 of 15). Below 1.0 and not declared stable (0). 14+5+8+5+0 = 32.", "b": "Local-software lines, as a server the owner runs. `memmachine-server` and `memmachine-client` on PyPI with Python versions stated, a Docker image and a compose script (20). pytest, integration and installation-test workflows exist, but GitHub's API answered with a rate limit, so run results were unread (15 of 25, unchecked). 292 open issues and pull requests; the newest bug reports, including a 429 from a provider surfacing as a 500 and a 0.4.0 configuration that no longer starts, have zero to two replies (10 of 25). No changelog file, release notes only on GitHub, which weren't read, and pre-1.0 tags (6 of 15). Version 0.4.0 (0). Total 51." }, "scores": { "a": 32, "b": 51 } }, { "by": 6, "category": "transparency", "leads": "langmem", "name": "Transparency \u0026 trust", "reasons": { "a": "MIT licence in the repository and on PyPI (30). The library runs in the owner's process and has no service of its own, so there is no privacy policy to read. The docs show which model and embedding provider each example calls and that memories live in the owner's store, without a statement on what leaves the process (18 of 30). No deprecation policy or dated notices were found (0 of 20). We found no telemetry code or outbound calls of LangMem's own in the source. Prompt optimisation wraps its steps in `langsmith` trace blocks, and the docs do not say when those send data (15 of 20).", "b": "Apache-2.0 (30). The terms say hosted customer data is destroyed on termination, with no period, and use usage data only in aggregate; the privacy policy wasn't read (12 of 30). No deprecation policy or notices found (3 of 20). No telemetry calls found in the server or client source, and the docs don't address it (10 of 20). Total 55." }, "scores": { "a": 63, "b": 57 } } ], "facts": [ { "a": "SDK + MCP", "b": "HTTP API", "name": "Kind" }, { "a": "LangChain", "b": "MemVerge, Inc.", "name": "Vendor" }, { "a": "no (local only)", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "", "b": "HTTP, stdio, Streamable HTTP", "name": "Transports" }, { "a": "None", "b": "None", "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": "3", "name": "Tools exposed" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "yes", "name": "llms.txt" }, { "a": "2025-10-27", "b": "2026-10-08", "name": "Last release" }, { "a": "no document linked", "b": "no date given", "name": "Terms last updated" }, { "a": "no document linked", "b": "2026-05-20", "name": "Privacy policy last updated" }, { "a": "not read yet", "b": "not found in the text", "name": "Customer content may train models" }, { "a": "not read yet", "b": "yes", "name": "Terms restrict automated access" }, { "a": "not read yet", "b": "yes", "name": "Terms restrict benchmarking" }, { "a": "not read yet", "b": "not found in the text", "name": "Terms or service can change without notice" }, { "a": "not read yet", "b": "yes", "name": "Arbitration or class-action waiver" }, { "a": "1.7k stars", "b": "3.1k stars, 28 npm/wk, 581 PyPI/wk", "name": "Popularity" }, { "a": "2.8/5 (4)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "MemMachine scores 58 (C) on agent readiness against LangMem's 47.7 (D), and leads in 3 of 7 scored categories. LangMem leads on payments \u0026 pricing and transparency \u0026 trust.", "question": "Which is better for AI agents, LangMem or MemMachine?" }, { "answer": "No hosted endpoint is listed for LangMem. MemMachine runs on your own machine, with no hosted endpoint listed.", "question": "Can an agent call LangMem and MemMachine without installing anything?" }, { "answer": "Yes. LangMem is open source (MIT). MemMachine is open source (Apache-2.0).", "question": "Are LangMem and MemMachine open source?" } ], "goodFor": [ { "aheadOn": [ "Payments \u0026 pricing, 60 against 40", "Transparency \u0026 trust, 63 against 57" ], "also": null, "goodFor": "Teams already on LangGraph that want memory tools and background extraction over a store they run.", "slug": "langmem", "watchFor": "No release found in over a year. The newest version, 0.0.30, was set on 9 September 2025, and no commit has changed `src` since 28 July 2025" }, { "aheadOn": [ "Reliability, 51 against 32", "Schema \u0026 documentation, 79 against 55", "Maintenance \u0026 community, 83 against 15" ], "also": [ "Runs on your own machine" ], "goodFor": "Self-hosted memory for agent frameworks that want episodic and profile memory with many integrations.", "slug": "memmachine", "watchFor": "Version 0.4.0 of 6 October 2026, pre-1.0, with no changelog file in the repository" } ], "history": { "langmem": [ { "causes": [ "correction" ], "date": "2026-11-04", "delta": -0.6, "from": 48.3, "fromGrade": "D", "to": 47.7, "toGrade": "D" }, { "causes": [ "method" ], "date": "2026-10-27", "delta": 0.4, "from": 47.9, "fromGrade": "D", "to": 48.3, "toGrade": "D" } ], "memmachine": null }, "job": { "capability": "memory.store", "name": "Agent memory" }, "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-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/basic-memory-vs-langmem.json", "title": "Basic Memory vs LangMem", "url": "https://www.anchorterminal.com/compare/basic-memory-vs-langmem" }, { "json": "https://www.anchorterminal.com/compare/basic-memory-vs-memmachine.json", "title": "Basic Memory vs MemMachine", "url": "https://www.anchorterminal.com/compare/basic-memory-vs-memmachine" }, { "json": "https://www.anchorterminal.com/compare/claude-mem-vs-langmem.json", "title": "claude-mem vs LangMem", "url": "https://www.anchorterminal.com/compare/claude-mem-vs-langmem" }, { "json": "https://www.anchorterminal.com/compare/claude-mem-vs-memmachine.json", "title": "claude-mem vs MemMachine", "url": "https://www.anchorterminal.com/compare/claude-mem-vs-memmachine" }, { "json": "https://www.anchorterminal.com/compare/cognee-vs-langmem.json", "title": "Cognee vs LangMem", "url": "https://www.anchorterminal.com/compare/cognee-vs-langmem" }, { "json": "https://www.anchorterminal.com/compare/cognee-vs-memmachine.json", "title": "Cognee vs MemMachine", "url": "https://www.anchorterminal.com/compare/cognee-vs-memmachine" }, { "json": "https://www.anchorterminal.com/compare/everos-vs-langmem.json", "title": "EverOS vs LangMem", "url": "https://www.anchorterminal.com/compare/everos-vs-langmem" }, { "json": "https://www.anchorterminal.com/compare/everos-vs-memmachine.json", "title": "EverOS vs MemMachine", "url": "https://www.anchorterminal.com/compare/everos-vs-memmachine" }, { "json": "https://www.anchorterminal.com/compare/google-memory-bank-vs-langmem.json", "title": "Agent Platform Memory Bank vs LangMem", "url": "https://www.anchorterminal.com/compare/google-memory-bank-vs-langmem" }, { "json": "https://www.anchorterminal.com/compare/google-memory-bank-vs-memmachine.json", "title": "Agent Platform Memory Bank vs MemMachine", "url": "https://www.anchorterminal.com/compare/google-memory-bank-vs-memmachine" }, { "json": "https://www.anchorterminal.com/compare/graphiti-vs-langmem.json", "title": "Graphiti vs LangMem", "url": "https://www.anchorterminal.com/compare/graphiti-vs-langmem" }, { "json": "https://www.anchorterminal.com/compare/graphiti-vs-memmachine.json", "title": "Graphiti vs MemMachine", "url": "https://www.anchorterminal.com/compare/graphiti-vs-memmachine" }, { "json": "https://www.anchorterminal.com/compare/hindsight-vs-langmem.json", "title": "Hindsight vs LangMem", "url": "https://www.anchorterminal.com/compare/hindsight-vs-langmem" }, { "json": "https://www.anchorterminal.com/compare/hindsight-vs-memmachine.json", "title": "Hindsight vs MemMachine", "url": "https://www.anchorterminal.com/compare/hindsight-vs-memmachine" }, { "json": "https://www.anchorterminal.com/compare/honcho-vs-langmem.json", "title": "Honcho vs LangMem", "url": "https://www.anchorterminal.com/compare/honcho-vs-langmem" }, { "json": "https://www.anchorterminal.com/compare/honcho-vs-memmachine.json", "title": "Honcho vs MemMachine", "url": "https://www.anchorterminal.com/compare/honcho-vs-memmachine" }, { "json": "https://www.anchorterminal.com/compare/hy-memory-vs-langmem.json", "title": "Hy Memory vs LangMem", "url": "https://www.anchorterminal.com/compare/hy-memory-vs-langmem" }, { "json": "https://www.anchorterminal.com/compare/hy-memory-vs-memmachine.json", "title": "Hy Memory vs MemMachine", "url": "https://www.anchorterminal.com/compare/hy-memory-vs-memmachine" }, { "json": "https://www.anchorterminal.com/compare/langmem-vs-localghost.json", "title": "LangMem vs LocalGhost", "url": "https://www.anchorterminal.com/compare/langmem-vs-localghost" }, { "json": "https://www.anchorterminal.com/compare/langmem-vs-mem0.json", "title": "LangMem vs Mem0 Platform + MCP", "url": "https://www.anchorterminal.com/compare/langmem-vs-mem0" }, { "json": "https://www.anchorterminal.com/compare/langmem-vs-memori.json", "title": "LangMem vs Memori", "url": "https://www.anchorterminal.com/compare/langmem-vs-memori" }, { "json": "https://www.anchorterminal.com/compare/langmem-vs-memory-reference-server.json", "title": "LangMem vs Memory (MCP reference server)", "url": "https://www.anchorterminal.com/compare/langmem-vs-memory-reference-server" }, { "json": "https://www.anchorterminal.com/compare/langmem-vs-mempalace.json", "title": "LangMem vs MemPalace", "url": "https://www.anchorterminal.com/compare/langmem-vs-mempalace" }, { "json": "https://www.anchorterminal.com/compare/langmem-vs-past-dev.json", "title": "LangMem vs past.dev", "url": "https://www.anchorterminal.com/compare/langmem-vs-past-dev" }, { "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-tencentdb-agent-memory.json", "title": "LangMem vs TencentDB Agent Memory", "url": "https://www.anchorterminal.com/compare/langmem-vs-tencentdb-agent-memory" }, { "json": "https://www.anchorterminal.com/compare/langmem-vs-tokenrip.json", "title": "LangMem vs Tokenrip", "url": "https://www.anchorterminal.com/compare/langmem-vs-tokenrip" }, { "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-memmachine.json", "title": "LocalGhost vs MemMachine", "url": "https://www.anchorterminal.com/compare/localghost-vs-memmachine" }, { "json": "https://www.anchorterminal.com/compare/mem0-vs-memmachine.json", "title": "Mem0 Platform + MCP vs MemMachine", "url": "https://www.anchorterminal.com/compare/mem0-vs-memmachine" }, { "json": "https://www.anchorterminal.com/compare/memmachine-vs-memori.json", "title": "MemMachine vs Memori", "url": "https://www.anchorterminal.com/compare/memmachine-vs-memori" }, { "json": "https://www.anchorterminal.com/compare/memmachine-vs-memory-reference-server.json", "title": "MemMachine vs Memory (MCP reference server)", "url": "https://www.anchorterminal.com/compare/memmachine-vs-memory-reference-server" }, { "json": "https://www.anchorterminal.com/compare/memmachine-vs-mempalace.json", "title": "MemMachine vs MemPalace", "url": "https://www.anchorterminal.com/compare/memmachine-vs-mempalace" }, { "json": "https://www.anchorterminal.com/compare/memmachine-vs-past-dev.json", "title": "MemMachine vs past.dev", "url": "https://www.anchorterminal.com/compare/memmachine-vs-past-dev" }, { "json": "https://www.anchorterminal.com/compare/memmachine-vs-supermemory.json", "title": "MemMachine vs Supermemory API + MCP", "url": "https://www.anchorterminal.com/compare/memmachine-vs-supermemory" }, { "json": "https://www.anchorterminal.com/compare/memmachine-vs-tencentdb-agent-memory.json", "title": "MemMachine vs TencentDB Agent Memory", "url": "https://www.anchorterminal.com/compare/memmachine-vs-tencentdb-agent-memory" }, { "json": "https://www.anchorterminal.com/compare/memmachine-vs-tokenrip.json", "title": "MemMachine vs Tokenrip", "url": "https://www.anchorterminal.com/compare/memmachine-vs-tokenrip" }, { "json": "https://www.anchorterminal.com/compare/memmachine-vs-zep.json", "title": "MemMachine vs Zep", "url": "https://www.anchorterminal.com/compare/memmachine-vs-zep" }, { "json": "https://www.anchorterminal.com/compare/ai-memory-vs-langmem.json", "title": "AI Memory vs LangMem", "url": "https://www.anchorterminal.com/compare/ai-memory-vs-langmem" }, { "json": "https://www.anchorterminal.com/compare/ai-memory-vs-memmachine.json", "title": "AI Memory vs MemMachine", "url": "https://www.anchorterminal.com/compare/ai-memory-vs-memmachine" }, { "json": "https://www.anchorterminal.com/compare/context-mode-vs-langmem.json", "title": "Context Mode Engine vs LangMem", "url": "https://www.anchorterminal.com/compare/context-mode-vs-langmem" }, { "json": "https://www.anchorterminal.com/compare/context-mode-vs-memmachine.json", "title": "Context Mode Engine vs MemMachine", "url": "https://www.anchorterminal.com/compare/context-mode-vs-memmachine" }, { "json": "https://www.anchorterminal.com/compare/graphicle-vs-langmem.json", "title": "Graphicle vs LangMem", "url": "https://www.anchorterminal.com/compare/graphicle-vs-langmem" }, { "json": "https://www.anchorterminal.com/compare/graphicle-vs-memmachine.json", "title": "Graphicle vs MemMachine", "url": "https://www.anchorterminal.com/compare/graphicle-vs-memmachine" } ], "panel": null, "scores": [ { "by": 19, "edge": "memmachine", "key": "reliability", "langmem": 32, "memmachine": 51, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 24, "edge": "memmachine", "key": "schema", "langmem": 55, "memmachine": 79, "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 1, "edge": "langmem", "key": "ergonomics", "langmem": 66, "memmachine": 65, "name": "Agent ergonomics", "weight": 13 }, { "by": 1, "edge": "langmem", "key": "security", "langmem": 42, "memmachine": 41, "name": "Security \u0026 auth", "weight": 14 }, { "by": 20, "edge": "langmem", "key": "payments", "langmem": 60, "memmachine": 40, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 68, "edge": "memmachine", "key": "maintenance", "langmem": 15, "memmachine": 83, "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 6, "edge": "langmem", "key": "transparency", "langmem": 63, "memmachine": 57, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "MemMachine scores 58 (C) on agent readiness against LangMem's 47.7 (D), and leads in 3 of 7 scored categories. LangMem leads on payments \u0026 pricing and transparency \u0026 trust. Both do agent memory.", "tasks": null, "tutorials": [], "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 version, 0.0.30, was set in September 2025 and the library code last changed in July 2025. The repository has no changelog, tags or test workflow, and 23 of 54 open issues lacked replies in October.", "memmachine": "MemMachine is an Apache-2.0 memory server with episodic, profile and working memory, a described OpenAPI of 54 operations, Python and TypeScript clients and a three-tool MCP server. It is version 0.4.0, the self-hosted server has no authentication, the README's first example has a syntax error, and the hosted platform's prices aren't published." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/langmem-vs-memmachine", "json": "https://www.anchorterminal.com/compare/langmem-vs-memmachine.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/langmem-vs-memmachine.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/langmem-vs-memmachine.min.md" }, "markdown": "MemMachine scores 58 (C) on agent readiness against LangMem's 47.7 (D), and leads in 3 of 7 scored categories. LangMem leads on payments \u0026 pricing and transparency \u0026 trust. Both do agent memory.\n\n- LangMem: grade D, 47.7/100, rank #1132 of 1486. Markdown https://www.anchorterminal.com/tools/langmem.md · JSON https://www.anchorterminal.com/api/v1/tools/langmem.json\n- MemMachine: grade C, 58/100, rank #767 of 1486. Markdown https://www.anchorterminal.com/tools/memmachine.md · JSON https://www.anchorterminal.com/api/v1/tools/memmachine.json\n- Best memory layers for AI agents: https://www.anchorterminal.com/best/agent-memory/index.md\n- All 353 memory comparisons: https://www.anchorterminal.com/compare/agent-memory/index.md\n\n## Which one, for what\n\n### 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 40\n- Transparency \u0026 trust, 63 against 57\n\nWatch for: No release found in over a year. The newest version, 0.0.30, was set on 9 September 2025, and no commit has changed `src` since 28 July 2025\n\n### MemMachine (C)\n\nGood for: Self-hosted memory for agent frameworks that want episodic and profile memory with many integrations.\n\nAhead on:\n- Reliability, 51 against 32\n- Schema \u0026 documentation, 79 against 55\n- Maintenance \u0026 community, 83 against 15\n\nAlso in its favour:\n- Runs on your own machine\n\nWatch for: Version 0.4.0 of 6 October 2026, pre-1.0, with no changelog file in the repository\n\n\n## Why the edge\n\n### Maintenance \u0026 community: MemMachine +68\n\n- LangMem (15): No release found in the last 180 days. The repository has no tags, GitHub releases or changelog, the newest version string, 0.0.30, was set in `pyproject.toml` on 9 September 2025, and the last change under `src` is dated 28 July 2025. PyPI's release dates could not be read on 4 November (0). No release in the last 90 days (0). Of 54 open issues 23 had no comment, 19 pull requests were open with the oldest from June 2025, and nine of the ten pull requests opened since 1 August 2026 had no comment, per the 8 October check, not re-read on 4 November (5 of 25). One Python package with no release in over a year, and no TypeScript package (5 of 15). Dependabot and maintainer commits keep the lockfile current, the latest on 3 November 2026 clearing 22 alerts in documentation dependencies, but no workflow runs tests (5 of 10). 0+0+5+5+5 = 15.\n- MemMachine (83): v0.4.0 on PyPI on 8 October 2026, 29 days before the check (30). v0.3.9-post1, v0.4.0, v0.4.1-dev0 and v0.4.1-a1 in 90 days (20). Many open issues and recent reports with few replies (12 of 25). Python and TypeScript clients, both current (12 of 15). uv lock checks, security audit, SBOM and stale-issue workflows (9 of 10). Total 83.\n\n### Schema \u0026 documentation: MemMachine +24\n\n- LangMem (55): Library reading, with the tool lines applied to the two agent tools. No OpenAPI applies. Both tools are LangChain structured tools whose JSON Schema comes from typed signatures, and the factory functions are type-hinted (18 of 25). langchain-ai.github.io/langmem/llms.txt returns 404 (0). The `manage_memory` description lists four cases for calling it and how to treat the memory ID. `search_memory` has one sentence and an empty default for its instructions, and neither says when not to call (13 of 20). `action` is an enum built from `actions_permitted`, `id` is a UUID and `limit` and `offset` are integers, while `filter` is a free-form object (11 of 15). Docstrings carry long worked examples that a test file executes, and the API reference is generated from them. Error behaviour is not documented (10 of 15). Version numbers exist only on PyPI, with no changelog (3 of 15).\n- MemMachine (79): OpenAPI documents for the server (54 operations) and the hosted platform (12) (25). llms.txt on docs.memmachine.ai with Markdown pages (10). Every operation has a description, and the docs explain memory types and scoping (15 of 20). Typed request models generated from the server, with search options for limits and filters (12 of 15). Examples for each client and the MCP tools, but only 422 is documented on the server and the README's first example doesn't run (8 of 15). `/api/v2` paths and tagged releases, no changelog (9 of 15). Total 79.\n\n### Payments \u0026 pricing: LangMem +20\n\n- LangMem (60): MIT-licensed package the owner runs, with nothing to buy for LangMem itself, read with the self-hosted rule. 20 for pricing, 20 for a free start and 20 for use without an account. No x402, MPP or L402 in the docs or source (0). LLM, embedding and database costs are the owner's.\n- MemMachine (40): Self-hosted rule, with the price lines read for the hosted platform. No x402, MPP or L402 (0 of 40). No hosted prices found on the site or docs (0). Free to self-host with no card (20). An agent can install it from PyPI with no account (20). Total 40.\n\n### Reliability: MemMachine +19\n\n- LangMem (32): Local-software reading. Installs from PyPI as `langmem` with Python 3.10 or later declared, but `extraction.py` on main uses `typing.NotRequired`, which arrived in Python 3.11, and issues 81 and 83 about failed imports on 3.10 are open (per the 8 October check). We read the source and did not run it on 3.10 (14 of 20). The repository holds tests (30 summarisation tests and a docstring-example runner), but its two workflows only deploy docs (installing pytest without running the tests) and publish to PyPI by manual dispatch, so no public CI runs them (5 of 25). 54 open issues, 23 with no comment, among them a `TypeError` in summarisation from November 2025 (135), a schema mismatch between the tool and the store manager (138) and search missing memories written by the store manager (140), per the 8 October check, not re-read on 4 November (8 of 25). Versions are 0.0.x with no changelog, GitHub releases or tags, and open issue 130 shows 0.0.30 was cut to restore compatibility with LangGraph 1.0 (5 of 15). Below 1.0 and not declared stable (0). 14+5+8+5+0 = 32.\n- MemMachine (51): Local-software lines, as a server the owner runs. `memmachine-server` and `memmachine-client` on PyPI with Python versions stated, a Docker image and a compose script (20). pytest, integration and installation-test workflows exist, but GitHub's API answered with a rate limit, so run results were unread (15 of 25, unchecked). 292 open issues and pull requests; the newest bug reports, including a 429 from a provider surfacing as a 500 and a 0.4.0 configuration that no longer starts, have zero to two replies (10 of 25). No changelog file, release notes only on GitHub, which weren't read, and pre-1.0 tags (6 of 15). Version 0.4.0 (0). Total 51.\n\n### Transparency \u0026 trust: LangMem +6\n\n- LangMem (63): MIT licence in the repository and on PyPI (30). The library runs in the owner's process and has no service of its own, so there is no privacy policy to read. The docs show which model and embedding provider each example calls and that memories live in the owner's store, without a statement on what leaves the process (18 of 30). No deprecation policy or dated notices were found (0 of 20). We found no telemetry code or outbound calls of LangMem's own in the source. Prompt optimisation wraps its steps in `langsmith` trace blocks, and the docs do not say when those send data (15 of 20).\n- MemMachine (57): Apache-2.0 (30). The terms say hosted customer data is destroyed on termination, with no period, and use usage data only in aggregate; the privacy policy wasn't read (12 of 30). No deprecation policy or notices found (3 of 20). No telemetry calls found in the server or client source, and the docs don't address it (10 of 20). Total 55.\n\n## Score by category\n\n| Category | Weight | LangMem | MemMachine | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 32 | 51 | MemMachine +19 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 55 | 79 | MemMachine +24 |\n| Agent ergonomics | 13% (16.2 this run) | 66 | 65 | LangMem +1 |\n| Security \u0026 auth | 14% (17.5 this run) | 42 | 41 | LangMem +1 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 60 | 40 | LangMem +20 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 15 | 83 | MemMachine +68 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 63 | 57 | LangMem +6 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **47.7 · D** | **58 · C** | |\n\n## Facts side by side\n\n| Fact | LangMem | MemMachine |\n| --- | --- | --- |\n| Kind | SDK + MCP | HTTP API |\n| Vendor | LangChain | MemVerge, Inc. |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | | HTTP, stdio, Streamable HTTP |\n| Auth | None | None |\n| Pricing | Free | Freemium |\n| x402 | no | no |\n| Licence | MIT | Apache-2.0 |\n| Tools exposed | none | 3 |\n| Read-only variant documented | no | no |\n| llms.txt | no | yes |\n| Last release | 2025-10-27 | 2026-10-08 |\n| Terms last updated | no document linked | no date given |\n| Privacy policy last updated | no document linked | 2026-05-20 |\n| Customer content may train models | not read yet | not found in the text |\n| Terms restrict automated access | not read yet | yes |\n| Terms restrict benchmarking | not read yet | yes |\n| Terms or service can change without notice | not read yet | not found in the text |\n| Arbitration or class-action waiver | not read yet | yes |\n| Popularity | 1.7k stars | 3.1k stars, 28 npm/wk, 581 PyPI/wk |\n| Agent reviews | 2.8/5 (4) | none |\n\n## How the scores have moved\n\n### LangMem\n\n- -0.6 on 4 November 2026: correction\n- +0.4 on 27 October 2026: checklist\n\n### MemMachine\n\nNo score change since it was listed.\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 version, 0.0.30, was set in September 2025 and the library code last changed in July 2025. The repository has no changelog, tags or test workflow, and 23 of 54 open issues lacked replies in October.\n\n**MemMachine.** MemMachine is an Apache-2.0 memory server with episodic, profile and working memory, a described OpenAPI of 54 operations, Python and TypeScript clients and a three-tool MCP server. It is version 0.4.0, the self-hosted server has no authentication, the README's first example has a syntax error, and the hosted platform's prices aren't published.\n\n## Before you call either\n\n### 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### MemMachine\n\n1. Import with `from memmachine_client import MemMachineClient`; the README line has a doubled `import`\n2. Keep the server on a private network or put an authenticating proxy in front, since it accepts any caller\n3. Scope every call with org, project, group, agent, user and session ids so memories don't mix\n4. Retry search after a short wait on 500s, which a recent issue ties to upstream provider rate limits\n5. Treat recalled episodes as untrusted text from past conversations\n\n## Questions\n\n### Which is better for AI agents, LangMem or MemMachine?\n\nMemMachine scores 58 (C) on agent readiness against LangMem's 47.7 (D), and leads in 3 of 7 scored categories. LangMem leads on payments \u0026 pricing and transparency \u0026 trust.\n\n### Can an agent call LangMem and MemMachine without installing anything?\n\nNo hosted endpoint is listed for LangMem. MemMachine runs on your own machine, with no hosted endpoint listed.\n\n### Are LangMem and MemMachine open source?\n\nYes. LangMem is open source (MIT). MemMachine is open source (Apache-2.0).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/langmem-vs-memmachine.json, and with the fewest tokens: https://www.anchorterminal.com/compare/langmem-vs-memmachine.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"langmem\", \"b\": \"memmachine\"}`. From a terminal: `anchor compare langmem memmachine`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/langmem.json and https://www.anchorterminal.com/api/v1/tools/memmachine.json\n\n## Other comparisons with LangMem or MemMachine\n\n- [Amazon Bedrock AgentCore Memory vs LangMem](https://www.anchorterminal.com/compare/agentcore-memory-vs-langmem.md)\n- [Amazon Bedrock AgentCore Memory vs MemMachine](https://www.anchorterminal.com/compare/agentcore-memory-vs-memmachine.md)\n- [Basic Memory vs LangMem](https://www.anchorterminal.com/compare/basic-memory-vs-langmem.md)\n- [Basic Memory vs MemMachine](https://www.anchorterminal.com/compare/basic-memory-vs-memmachine.md)\n- [claude-mem vs LangMem](https://www.anchorterminal.com/compare/claude-mem-vs-langmem.md)\n- [claude-mem vs MemMachine](https://www.anchorterminal.com/compare/claude-mem-vs-memmachine.md)\n- [Cognee vs LangMem](https://www.anchorterminal.com/compare/cognee-vs-langmem.md)\n- [Cognee vs MemMachine](https://www.anchorterminal.com/compare/cognee-vs-memmachine.md)\n- [EverOS vs LangMem](https://www.anchorterminal.com/compare/everos-vs-langmem.md)\n- [EverOS vs MemMachine](https://www.anchorterminal.com/compare/everos-vs-memmachine.md)\n- [Agent Platform Memory Bank vs LangMem](https://www.anchorterminal.com/compare/google-memory-bank-vs-langmem.md)\n- [Agent Platform Memory Bank vs MemMachine](https://www.anchorterminal.com/compare/google-memory-bank-vs-memmachine.md)\n- [Graphiti vs LangMem](https://www.anchorterminal.com/compare/graphiti-vs-langmem.md)\n- [Graphiti vs MemMachine](https://www.anchorterminal.com/compare/graphiti-vs-memmachine.md)\n- [Hindsight vs LangMem](https://www.anchorterminal.com/compare/hindsight-vs-langmem.md)\n- [Hindsight vs MemMachine](https://www.anchorterminal.com/compare/hindsight-vs-memmachine.md)\n- [Honcho vs LangMem](https://www.anchorterminal.com/compare/honcho-vs-langmem.md)\n- [Honcho vs MemMachine](https://www.anchorterminal.com/compare/honcho-vs-memmachine.md)\n- [Hy Memory vs LangMem](https://www.anchorterminal.com/compare/hy-memory-vs-langmem.md)\n- [Hy Memory vs MemMachine](https://www.anchorterminal.com/compare/hy-memory-vs-memmachine.md)\n- [LangMem vs LocalGhost](https://www.anchorterminal.com/compare/langmem-vs-localghost.md)\n- [LangMem vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/langmem-vs-mem0.md)\n- [LangMem vs Memori](https://www.anchorterminal.com/compare/langmem-vs-memori.md)\n- [LangMem vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/langmem-vs-memory-reference-server.md)\n- [LangMem vs MemPalace](https://www.anchorterminal.com/compare/langmem-vs-mempalace.md)\n- [LangMem vs past.dev](https://www.anchorterminal.com/compare/langmem-vs-past-dev.md)\n- [LangMem vs Supermemory API + MCP](https://www.anchorterminal.com/compare/langmem-vs-supermemory.md)\n- [LangMem vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/langmem-vs-tencentdb-agent-memory.md)\n- [LangMem vs Tokenrip](https://www.anchorterminal.com/compare/langmem-vs-tokenrip.md)\n- [LangMem vs Zep](https://www.anchorterminal.com/compare/langmem-vs-zep.md)\n- [LocalGhost vs MemMachine](https://www.anchorterminal.com/compare/localghost-vs-memmachine.md)\n- [Mem0 Platform + MCP vs MemMachine](https://www.anchorterminal.com/compare/mem0-vs-memmachine.md)\n- [MemMachine vs Memori](https://www.anchorterminal.com/compare/memmachine-vs-memori.md)\n- [MemMachine vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/memmachine-vs-memory-reference-server.md)\n- [MemMachine vs MemPalace](https://www.anchorterminal.com/compare/memmachine-vs-mempalace.md)\n- [MemMachine vs past.dev](https://www.anchorterminal.com/compare/memmachine-vs-past-dev.md)\n- [MemMachine vs Supermemory API + MCP](https://www.anchorterminal.com/compare/memmachine-vs-supermemory.md)\n- [MemMachine vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/memmachine-vs-tencentdb-agent-memory.md)\n- [MemMachine vs Tokenrip](https://www.anchorterminal.com/compare/memmachine-vs-tokenrip.md)\n- [MemMachine vs Zep](https://www.anchorterminal.com/compare/memmachine-vs-zep.md)\n- [AI Memory vs LangMem](https://www.anchorterminal.com/compare/ai-memory-vs-langmem.md)\n- [AI Memory vs MemMachine](https://www.anchorterminal.com/compare/ai-memory-vs-memmachine.md)\n- [Context Mode Engine vs LangMem](https://www.anchorterminal.com/compare/context-mode-vs-langmem.md)\n- [Context Mode Engine vs MemMachine](https://www.anchorterminal.com/compare/context-mode-vs-memmachine.md)\n- [Graphicle vs LangMem](https://www.anchorterminal.com/compare/graphicle-vs-langmem.md)\n- [Graphicle vs MemMachine](https://www.anchorterminal.com/compare/graphicle-vs-memmachine.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit 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