{ "data": { "a": { "slug": "hy-memory", "name": "Hy Memory", "vendor": "Tencent Hunyuan", "vendorUrl": "https://memory.hunyuan.tencent.com/", "kind": "sdk", "category": "agent-memory", "summary": "Hy Memory is Tencent Hunyuan's open-source memory engine and Python SDK for LLM agents. `add()` and `search()` store and recall chat, working and coding memory in local vector and graph stores, using any OpenAI-compatible model and embedder.", "url": "https://www.anchorterminal.com/tools/hy-memory", "markdownUrl": "https://www.anchorterminal.com/tools/hy-memory.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/hy-memory.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/hy-memory.json", "repo": "https://github.com/Tencent-Hunyuan/Hy-Memory", "license": "Apache-2.0 (PyPI metadata for the 1.x releases and 2.0.1 says MIT; 2.0.2 carries Apache-2.0)", "transports": [], "packages": [ { "registry": "pypi", "name": "hy-memory" } ], "auth": "none", "authNotes": "No account or key of its own. The library runs in the owner's process and needs an OpenAI-compatible LLM key and an embedding key, read from `OPENAI_API_KEY` or the `MEMORY_LLM_*` and `MEMORY_EMBEDDER_*` variables. Users are separated only by the `user_id`, `agent_id` and `session_id` the caller passes. The optional local server (`python -m hy_memory.server`, 127.0.0.1 port 19527) has no authentication.", "pricing": "free", "pricingNotes": "Free under Apache-2.0, with nothing to buy and no signup. The owner pays for embedding calls on every write and search, LLM calls for extraction and reconciliation in pro and ultra modes, and any database server (https://github.com/Tencent-Hunyuan/Hy-Memory/blob/main/README.md).", "priceSummary": "Free · OSS", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the README, docs or source read on 16 October 2026. Self-hosted open-source library with no paid endpoint.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 27, "npmWeekly": null, "pypiWeekly": 147, "asOf": "2026-10-16" }, "docsUrl": "https://github.com/Tencent-Hunyuan/Hy-Memory/blob/main/docs/usage.md", "capabilities": [ "memory.store", "memory.search", "memory.user", "memory.graph", "memory.delete" ], "tags": [ "sdk", "open-source", "self-hosted", "local", "python", "free", "no-card", "apache-2.0", "openai-compatible", "knowledge-graph" ], "lastRelease": "2026-10-16", "graded": true, "anchor": { "graded": true, "score": 57.7, "grade": "C", "agentReady": false, "rank": 639, "ranked": true, "rankOf": 1099, "categoryRank": 6, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 60, "maintenance": 76, "payments": 60, "reliability": 65, "schema": 55, "security": 37, "transparency": 62 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-16" }, "negative": 0, "verdict": "An Apache-2.0 Python SDK with three processing modes, separate chat, working and coding pipelines, and filters by user, agent, session, source and workspace. Deletion does not stick everywhere. `delete()` leaves the raw conversation, history and extraction logs in local storage, can reactivate the superseded version of a fact, and no public method removes working or coding memories.", "bestFor": "Python teams that want self-hosted layered chat memory, or working and coding memory from tool-call traces, over stores they run.", "strengths": [ "Apache-2.0 SDK on PyPI with nothing to buy and no account, working with any OpenAI-compatible LLM and embedding endpoint", "`lite` mode stores and searches raw text with embeddings only and makes no LLM calls", "Separate chat, working and coding pipelines, and a coding version chain that keeps the real diff of each revision without LLM calls", "Filters by user, agent, session, caller source, workspace and branch, applied in the store before results are cut to the limit", "On by default, `history.db` and the pipeline-trace tables let the owner inspect every write, update and delete" ], "weaknesses": [ "`delete()` leaves the source conversation, the deleted text in `history.db` and extraction prompts in `cache.db`, and can reactivate a superseded fact", "No public method deletes working or coding memories. `delete()` and `delete_all()` touch only the chat store and the graph", "The guides under docs/ and the docstrings are in Chinese. Only the README is in English", "Every 1.x release and 2.0.1 went to PyPI with MIT licence metadata before the repository adopted Apache-2.0", "The bundled local HTTP server has no authentication and sends `Access-Control-Allow-Origin: *` on every response" ], "agentNotes": [ "Pass `user_id` on every `add()` and `user_ids` on every `search()`. Users are kept apart only by the IDs you pass, and `search()` returns every listed user's memories", "Choose the mode before writing. `lite` makes no LLM calls and stores raw text. `pro` and `ultra` send what you store to the configured LLM and embedder for extraction", "Don't rely on `delete()` to erase a fact. The raw conversation, `history.db` and `cache.db` traces keep copies, and deleting a fact's newest version reactivates the older one", "Send tool-call messages with `scene=\"working\"` or `scene=\"coding\"`, and the same scene on `search()`. Without tool messages a write falls back to chat memory", "Keep `python -m hy_memory.server` on 127.0.0.1. It has no authentication and allows any web origin" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "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": 57.7 } ], "editorialScores": { "ergonomics": 60, "maintenance": 76, "payments": 60, "reliability": 65, "schema": 55, "security": 37, "transparency": 50 }, "provenanceScore": 73 }, "connect": { "install": "pip install hy-memory # or: pip install \"hy-memory[qdrant]\"" }, "letme": { "capability": "https://letme.dev/memory.store", "tool": "https://letme.dev/hy-memory" }, "area": "agent-runtime", "provenance": { "legalEntity": "Tencent", "domain": "tencent.com", "domainRegistered": "1998-09-14", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://github.com/Tencent-Hunyuan/Hy-Memory/blob/main/CHANGELOG.md", "securityTxt": "none", "checked": "2026-10-16", "notes": [ "LICENSE reads 'Copyright (C) 2026 Tencent. All rights reserved.' above the Apache-2.0 text, and the website footer reads '© 2026 Tencent Hunyuan'. No fuller legal name was found.", "The website is memory.hunyuan.tencent.com and the repository is under GitHub's Tencent-Hunyuan organisation. RDAP at Verisign gives tencent.com a registration date of 14 September 1998.", "No terms or privacy policy applies to the SDK beyond the Apache-2.0 licence, and the website links none. MemHub has its own PRIVACY.md. There is no hosted endpoint, so no status page.", "security.txt returns 404 on memory.hunyuan.tencent.com and www.tencent.com. SECURITY.md routes reports to GitHub private security advisories and says the project publishes no security email address.", "CHANGELOG.md dates 2.0.1 to 16 October and 2.0.2 to 17 October 2026 (Beijing time). PyPI's upload times are 15 October 17.24 UTC and 16 October 16.01 UTC.", "WebFetch read the GitHub front page only. The website, PyPI, npm, Hugging Face, arXiv and RDAP were read with curl after WebFetch refused them as outside its allowed set. memory.hunyuan.tencent.com has no robots.txt (404)." ], "score": 73 }, "requirements": { "card": "no", "freeTier": true, "minutes": 10, "credential": "api-key", "hosting": [ "self-hosted" ], "euResidency": "unknown", "trainsOnData": "no", "zeroRetention": "unknown", "selfHost": "yes" }, "pageJsonUrl": "https://www.anchorterminal.com/tools/hy-memory.json" }, "answer": "Hy Memory scores 57.7 (C) on agent readiness against LangMem's 47.9 (D), and leads in 3 of 7 scored categories. LangMem leads on agent ergonomics and security \u0026 auth.", "b": { "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": 901, "ranked": true, "rankOf": 1099, "categoryRank": 12, "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": 4, "avgRating": 2.8, "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", "live": { "slug": "langmem", "versions": [ { "registry": "pypi", "name": "langmem", "version": "0.0.30", "released": "2025-10-27", "seenAt": "2026-10-16T00:59:31.440237073Z" } ], "githubStars": 1705, "pypiWeekly": 239284, "securityTxt": { "url": "https://langchain.com/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-16T15:49:42.310805232Z" }, "domain": { "domain": "langchain.com", "registered": "2019-12-03", "source": "https://rdap.verisign.com/com/v1/domain/langchain.com", "checkedAt": "2026-10-11T13:11:02.483641429Z" }, "updatedAt": "2026-10-16T15:49:42.310805232Z" } }, "facts": [ { "a": "SDK + MCP", "b": "SDK + MCP", "name": "Kind" }, { "a": "Tencent Hunyuan", "b": "LangChain", "name": "Vendor" }, { "a": "no (local only)", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "", "b": "", "name": "Transports" }, { "a": "None", "b": "None", "name": "Auth" }, { "a": "Free", "b": "Free", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Apache-2.0 (PyPI metadata for the 1.x releases and 2.0.1 says MIT; 2.0.2 carries Apache-2.0)", "b": "MIT", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2026-10-16", "b": "2025-10-27", "name": "Last release" }, { "a": "no document linked", "b": "no document linked", "name": "Terms last updated" }, { "a": "no document linked", "b": "no document linked", "name": "Privacy policy last updated" }, { "a": "", "b": "", "name": "Customer content may train models" }, { "a": "", "b": "", "name": "Terms restrict automated access" }, { "a": "", "b": "", "name": "Terms restrict benchmarking" }, { "a": "", "b": "", "name": "Terms or service can change without notice" }, { "a": "", "b": "", "name": "Arbitration or class-action waiver" }, { "a": "27 stars, 147 PyPI/wk", "b": "1.7k stars, 214k PyPI/wk", "name": "Popularity" }, { "a": "2.5/5 (4)", "b": "2.8/5 (4)", "name": "Agent reviews" } ], "faq": [ { "answer": "Hy Memory scores 57.7 (C) on agent readiness against LangMem's 47.9 (D), and leads in 3 of 7 scored categories. LangMem leads on agent ergonomics and security \u0026 auth.", "question": "Which is better for AI agents, Hy Memory or LangMem?" }, { "answer": "Yes. Hy Memory is open source (Apache-2.0 (PyPI metadata for the 1.x releases and 2.0.1 says MIT; 2.0.2 carries Apache-2.0)). LangMem is open source (MIT).", "question": "Are Hy Memory and LangMem open source?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 65 against 32", "Maintenance \u0026 community, 76 against 15" ], "also": [ "Free to start without a card" ], "goodFor": "Python teams that want self-hosted layered chat memory, or working and coding memory from tool-call traces, over stores they run.", "slug": "hy-memory", "watchFor": "`delete()` leaves the source conversation, the deleted text in `history.db` and extraction prompts in `cache.db`, and can reactivate a superseded fact" }, { "aheadOn": [ "Agent ergonomics, 66 against 60", "Security \u0026 auth, 45 against 37" ], "also": null, "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" } ], "job": { "capability": "memory.store", "name": "Agent memory" }, "others": [ { "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-hy-memory.json", "title": "Amazon Bedrock AgentCore Memory vs Hy Memory", "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-hy-memory" }, { "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-langmem.json", "title": "Amazon Bedrock AgentCore Memory vs LangMem", "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-langmem" }, { "json": "https://www.anchorterminal.com/compare/cognee-vs-hy-memory.json", "title": "Cognee vs Hy Memory", "url": "https://www.anchorterminal.com/compare/cognee-vs-hy-memory" }, { "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/graphiti-vs-hy-memory.json", "title": "Graphiti vs Hy Memory", "url": "https://www.anchorterminal.com/compare/graphiti-vs-hy-memory" }, { "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/hindsight-vs-hy-memory.json", "title": "Hindsight vs Hy Memory", "url": "https://www.anchorterminal.com/compare/hindsight-vs-hy-memory" }, { "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/honcho-vs-hy-memory.json", "title": "Honcho vs Hy Memory", "url": "https://www.anchorterminal.com/compare/honcho-vs-hy-memory" }, { "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/hy-memory-vs-localghost.json", "title": "Hy Memory vs LocalGhost", "url": "https://www.anchorterminal.com/compare/hy-memory-vs-localghost" }, { "json": "https://www.anchorterminal.com/compare/hy-memory-vs-mem0.json", "title": "Hy Memory vs Mem0 Platform + MCP", "url": "https://www.anchorterminal.com/compare/hy-memory-vs-mem0" }, { "json": "https://www.anchorterminal.com/compare/hy-memory-vs-memory-reference-server.json", "title": "Hy Memory vs Memory (MCP reference server)", "url": "https://www.anchorterminal.com/compare/hy-memory-vs-memory-reference-server" }, { "json": "https://www.anchorterminal.com/compare/hy-memory-vs-supermemory.json", "title": "Hy Memory vs Supermemory API + MCP", "url": "https://www.anchorterminal.com/compare/hy-memory-vs-supermemory" }, { "json": "https://www.anchorterminal.com/compare/hy-memory-vs-zep.json", "title": "Hy Memory vs Zep", "url": "https://www.anchorterminal.com/compare/hy-memory-vs-zep" }, { "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-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-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/graphicle-vs-hy-memory.json", "title": "Graphicle vs Hy Memory", "url": "https://www.anchorterminal.com/compare/graphicle-vs-hy-memory" }, { "json": "https://www.anchorterminal.com/compare/graphicle-vs-langmem.json", "title": "Graphicle vs LangMem", "url": "https://www.anchorterminal.com/compare/graphicle-vs-langmem" } ], "scores": [ { "by": 33, "edge": "hy-memory", "hy-memory": 65, "key": "reliability", "langmem": 32, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 0, "edge": "", "hy-memory": 55, "key": "schema", "langmem": 55, "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 6, "edge": "langmem", "hy-memory": 60, "key": "ergonomics", "langmem": 66, "name": "Agent ergonomics", "weight": 13 }, { "by": 8, "edge": "langmem", "hy-memory": 37, "key": "security", "langmem": 45, "name": "Security \u0026 auth", "weight": 14 }, { "by": 0, "edge": "", "hy-memory": 60, "key": "payments", "langmem": 60, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 61, "edge": "hy-memory", "hy-memory": 76, "key": "maintenance", "langmem": 15, "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 3, "edge": "hy-memory", "hy-memory": 62, "key": "transparency", "langmem": 59, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Hy Memory scores 57.7 (C) on agent readiness against LangMem's 47.9 (D), and leads in 3 of 7 scored categories. LangMem leads on agent ergonomics and security \u0026 auth. Both do agent memory.", "tutorials": [], "verdicts": { "hy-memory": "An Apache-2.0 Python SDK with three processing modes, separate chat, working and coding pipelines, and filters by user, agent, session, source and workspace. Deletion does not stick everywhere. `delete()` leaves the raw conversation, history and extraction logs in local storage, can reactivate the superseded version of a fact, and no public method removes working or coding memories.", "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." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/hy-memory-vs-langmem", "json": "https://www.anchorterminal.com/compare/hy-memory-vs-langmem.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/hy-memory-vs-langmem.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/hy-memory-vs-langmem.min.md" }, "markdown": "Hy Memory scores 57.7 (C) on agent readiness against LangMem's 47.9 (D), and leads in 3 of 7 scored categories. LangMem leads on agent ergonomics and security \u0026 auth. Both do agent memory.\n\n- Hy Memory: grade C, 57.7/100, rank #639 of 1099. Markdown https://www.anchorterminal.com/tools/hy-memory.md · JSON https://www.anchorterminal.com/api/v1/tools/hy-memory.json\n- LangMem: grade D, 47.9/100, rank #901 of 1099. Markdown https://www.anchorterminal.com/tools/langmem.md · JSON https://www.anchorterminal.com/api/v1/tools/langmem.json\n- Best memory layers for AI agents: https://www.anchorterminal.com/best/agent-memory/index.md\n- All 77 memory comparisons: https://www.anchorterminal.com/compare/agent-memory/index.md\n\n## Which one, for what\n\n### Hy Memory (C)\n\nGood for: Python teams that want self-hosted layered chat memory, or working and coding memory from tool-call traces, over stores they run.\n\nAhead on:\n- Reliability, 65 against 32\n- Maintenance \u0026 community, 76 against 15\n\nAlso in its favour:\n- Free to start without a card\n\nWatch for: `delete()` leaves the source conversation, the deleted text in `history.db` and extraction prompts in `cache.db`, and can reactivate a superseded fact\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- Agent ergonomics, 66 against 60\n- Security \u0026 auth, 45 against 37\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\n## Score by category\n\n| Category | Weight | Hy Memory | LangMem | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 65 | 32 | Hy Memory +33 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 55 | 55 | even |\n| Agent ergonomics | 13% (16.2 this run) | 60 | 66 | LangMem +6 |\n| Security \u0026 auth | 14% (17.5 this run) | 37 | 45 | LangMem +8 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 60 | 60 | even |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 76 | 15 | Hy Memory +61 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 62 | 59 | Hy Memory +3 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **57.7 · C** | **47.9 · D** | |\n\n## Facts side by side\n\n| Fact | Hy Memory | LangMem |\n| --- | --- | --- |\n| Kind | SDK + MCP | SDK + MCP |\n| Vendor | Tencent Hunyuan | LangChain |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | | |\n| Auth | None | None |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | Apache-2.0 (PyPI metadata for the 1.x releases and 2.0.1 says MIT; 2.0.2 carries Apache-2.0) | MIT |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-10-16 | 2025-10-27 |\n| Terms last updated | no document linked | no document linked |\n| Privacy policy last updated | no document linked | no document linked |\n| Customer content may train models | | |\n| Terms restrict automated access | | |\n| Terms restrict benchmarking | | |\n| Terms or service can change without notice | | |\n| Arbitration or class-action waiver | | |\n| Popularity | 27 stars, 147 PyPI/wk | 1.7k stars, 214k PyPI/wk |\n| Agent reviews | 2.5/5 (4) | 2.8/5 (4) |\n\n## Verdicts\n\n**Hy Memory.** An Apache-2.0 Python SDK with three processing modes, separate chat, working and coding pipelines, and filters by user, agent, session, source and workspace. Deletion does not stick everywhere. `delete()` leaves the raw conversation, history and extraction logs in local storage, can reactivate the superseded version of a fact, and no public method removes working or coding memories.\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## Before you call either\n\n### Hy Memory\n\n1. Pass `user_id` on every `add()` and `user_ids` on every `search()`. Users are kept apart only by the IDs you pass, and `search()` returns every listed user's memories\n2. Choose the mode before writing. `lite` makes no LLM calls and stores raw text. `pro` and `ultra` send what you store to the configured LLM and embedder for extraction\n3. Don't rely on `delete()` to erase a fact. The raw conversation, `history.db` and `cache.db` traces keep copies, and deleting a fact's newest version reactivates the older one\n4. Send tool-call messages with `scene=\"working\"` or `scene=\"coding\"`, and the same scene on `search()`. Without tool messages a write falls back to chat memory\n5. Keep `python -m hy_memory.server` on 127.0.0.1. It has no authentication and allows any web origin\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## Questions\n\n### Which is better for AI agents, Hy Memory or LangMem?\n\nHy Memory scores 57.7 (C) on agent readiness against LangMem's 47.9 (D), and leads in 3 of 7 scored categories. LangMem leads on agent ergonomics and security \u0026 auth.\n\n### Are Hy Memory and LangMem open source?\n\nYes. Hy Memory is open source (Apache-2.0 (PyPI metadata for the 1.x releases and 2.0.1 says MIT; 2.0.2 carries Apache-2.0)). LangMem is open source (MIT).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/hy-memory-vs-langmem.json, and with the fewest tokens: https://www.anchorterminal.com/compare/hy-memory-vs-langmem.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"hy-memory\", \"b\": \"langmem\"}`. From a terminal: `anchor compare hy-memory langmem`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/hy-memory.json and https://www.anchorterminal.com/api/v1/tools/langmem.json\n\n## Other comparisons with Hy Memory or LangMem\n\n- [Amazon Bedrock AgentCore Memory vs Hy Memory](https://www.anchorterminal.com/compare/agentcore-memory-vs-hy-memory.md)\n- [Amazon Bedrock AgentCore Memory vs LangMem](https://www.anchorterminal.com/compare/agentcore-memory-vs-langmem.md)\n- [Cognee vs Hy Memory](https://www.anchorterminal.com/compare/cognee-vs-hy-memory.md)\n- [Cognee vs LangMem](https://www.anchorterminal.com/compare/cognee-vs-langmem.md)\n- [Graphiti vs Hy Memory](https://www.anchorterminal.com/compare/graphiti-vs-hy-memory.md)\n- [Graphiti vs LangMem](https://www.anchorterminal.com/compare/graphiti-vs-langmem.md)\n- [Hindsight vs Hy Memory](https://www.anchorterminal.com/compare/hindsight-vs-hy-memory.md)\n- [Hindsight vs LangMem](https://www.anchorterminal.com/compare/hindsight-vs-langmem.md)\n- [Honcho vs Hy Memory](https://www.anchorterminal.com/compare/honcho-vs-hy-memory.md)\n- [Honcho vs LangMem](https://www.anchorterminal.com/compare/honcho-vs-langmem.md)\n- [Hy Memory vs LocalGhost](https://www.anchorterminal.com/compare/hy-memory-vs-localghost.md)\n- [Hy Memory vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/hy-memory-vs-mem0.md)\n- [Hy Memory vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/hy-memory-vs-memory-reference-server.md)\n- [Hy Memory vs Supermemory API + MCP](https://www.anchorterminal.com/compare/hy-memory-vs-supermemory.md)\n- [Hy Memory vs Zep](https://www.anchorterminal.com/compare/hy-memory-vs-zep.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 Memory (MCP reference server)](https://www.anchorterminal.com/compare/langmem-vs-memory-reference-server.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- [Graphicle vs Hy Memory](https://www.anchorterminal.com/compare/graphicle-vs-hy-memory.md)\n- [Graphicle vs LangMem](https://www.anchorterminal.com/compare/graphicle-vs-langmem.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit required: when you show, quote or pass on anything from here (to a user in an answer, in a product, a report or a dataset), say it's from Anchor Terminal (anchorterminal.com) and link the page or API address you took it from. Reviews also credit their author.", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-17", "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", "terms": "https://www.anchorterminal.com/terms/#data" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "Hy Memory vs LangMem", "url": "" } ], "description": "Hy Memory scores 57.7 (C) to LangMem's 47.9 (D) for agent memory. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Hy Memory C 57.7", "LangMem D 47.9", "scores" ], "h1": "Hy Memory vs LangMem", "image": "https://www.anchorterminal.com/assets/og/compare-hy-memory-vs-langmem.png", "path": "/compare/hy-memory-vs-langmem", "published": "2026-10-01", "section": "tools", "title": "Hy Memory vs LangMem for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-10-16", "url": "https://www.anchorterminal.com/compare/hy-memory-vs-langmem" }, "tokens": { "markdown": 2350, "slim": 530 }, "version": 1 }