{
  "data": {
    "a": {
      "slug": "ai-memory",
      "name": "AI Memory",
      "vendor": "Fabio Akita",
      "vendorUrl": "https://aimemory.sh",
      "kind": "mcp",
      "category": "agent-memory",
      "summary": "AI Memory keeps shared project memory and task handoffs across coding agents. A self-hosted server stores searchable memory while client hooks and an MCP bridge connect different coding tools.",
      "url": "https://www.anchorterminal.com/tools/ai-memory",
      "markdownUrl": "https://www.anchorterminal.com/tools/ai-memory.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/ai-memory.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/ai-memory.json",
      "repo": "https://github.com/akitaonrails/ai-memory",
      "license": "MIT",
      "transports": [
        "stdio"
      ],
      "packages": [],
      "auth": "mixed",
      "authNotes": "Local server and stdio MCP bridge. Fresh initialisation creates a root bearer token. Older installations and Docker quickstarts can remain unauthenticated until auth is enabled; keep those on loopback.",
      "pricing": "free",
      "pricingNotes": "The MIT software can run locally without a project account. Search has a zero-LLM mode; optional consolidation or configured model use can incur provider charges. Hosting costs are the operator’s responsibility.",
      "priceSummary": "Free",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "No machine payment protocol established in the reviewed project documentation.",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": 10684,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-19"
      },
      "docsUrl": "https://github.com/akitaonrails/ai-memory#readme",
      "capabilities": [
        "memory.search",
        "memory.write",
        "agent.handoff"
      ],
      "tags": [
        "agent-memory",
        "mcp",
        "free"
      ],
      "lastRelease": "2026-10-17",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 55.7,
        "grade": "C",
        "agentReady": false,
        "rank": 733,
        "ranked": true,
        "rankOf": 1171,
        "categoryRank": 9,
        "methodology": "0.4",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 65,
          "maintenance": 50,
          "payments": 60,
          "reliability": 50,
          "schema": 65,
          "security": 55,
          "transparency": 35
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-19"
        },
        "negative": 0,
        "verdict": "Cross-agent task handoffs and shared search. Existing deployments may still lack authentication.",
        "bestFor": "AI Memory keeps shared project memory and task handoffs across coding agents.",
        "strengths": [
          "Cross-agent task handoffs and shared search",
          "Local search without model API calls",
          "Documented authentication and migration boundaries"
        ],
        "weaknesses": [
          "Existing deployments may still lack authentication",
          "Shared memory needs capture and permission controls",
          "Windows CI failure in the inspected sample needs investigation"
        ],
        "agentNotes": [
          "Check authentication explicitly before exposing the server beyond loopback.",
          "Exclude secrets and sensitive repositories from memory capture.",
          "Back up memory and follow the version 3 migration guide."
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 3.5,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "C",
            "methodology": "0.4",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 55.7
          }
        ],
        "editorialScores": {
          "ergonomics": 65,
          "maintenance": 50,
          "payments": 60,
          "reliability": 50,
          "schema": 65,
          "security": 55,
          "transparency": 55
        },
        "provenanceScore": 14
      },
      "letme": {
        "capability": "https://letme.dev/memory.search",
        "tool": "https://letme.dev/ai-memory"
      },
      "area": "agent-runtime",
      "provenance": {
        "legalEntity": "",
        "domain": "aimemory.sh",
        "domainRegistered": "",
        "endpointOnVendorDomain": false,
        "terms": "https://raw.githubusercontent.com/akitaonrails/ai-memory/main/LICENSE",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://github.com/akitaonrails/ai-memory/releases",
        "securityTxt": "unknown",
        "checked": "2026-10-19",
        "notes": [
          "Assessment covers the named repository. No ownership claim or domain registration was verified."
        ],
        "score": 14
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/ai-memory.json"
    },
    "answer": "Hy Memory scores 57.7 (C) on agent readiness against AI Memory's 55.7 (C), and leads in 3 of 7 scored categories. AI Memory leads on schema \u0026 documentation, agent ergonomics and security \u0026 auth.",
    "b": {
      "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": 669,
        "ranked": true,
        "rankOf": 1171,
        "categoryRank": 7,
        "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",
      "live": {
        "slug": "hy-memory",
        "versions": [
          {
            "registry": "github",
            "name": "Tencent-Hunyuan/Hy-Memory",
            "version": "v1.0.4",
            "released": "2026-10-18",
            "seenAt": "2026-10-19T03:55:30.325991203Z"
          },
          {
            "registry": "pypi",
            "name": "hy-memory",
            "version": "2.0.4",
            "released": "2026-10-17",
            "seenAt": "2026-10-19T03:55:30.137315931Z"
          }
        ],
        "githubStars": 830,
        "pypiWeekly": 1469,
        "securityTxt": {
          "url": "https://tencent.com/.well-known/security.txt",
          "state": "unknown",
          "checkedAt": "2026-10-18T15:54:25.573430846Z"
        },
        "domain": {
          "domain": "tencent.com",
          "registered": "1998-09-14",
          "source": "https://rdap.verisign.com/com/v1/domain/tencent.com",
          "checkedAt": "2026-10-18T13:31:42.662620923Z"
        },
        "pages": [
          {
            "url": "https://raw.githubusercontent.com/Tencent-Hunyuan/Hy-Memory/main/CHANGELOG.md",
            "kind": "changelog",
            "status": 200,
            "checkedAt": "2026-10-18T23:36:55.718824303Z",
            "changedAt": "2026-10-18T23:36:55.718824303Z",
            "fingerprint": "b48c42865cb3"
          }
        ],
        "github": {
          "repo": "tencent-hunyuan/hy-memory",
          "checkedAt": "2026-10-19T06:53:32.002337139Z",
          "stars": 866,
          "archived": false,
          "issuesEnabled": true,
          "pushedAt": "2026-10-19T06:41:43Z",
          "openIssues": 16,
          "openPRs": 14,
          "issuesOpened90d": 34,
          "issuesClosed90d": 18,
          "prsMerged90d": 30,
          "ci": {
            "branch": "main",
            "runs": 29,
            "success": 21,
            "failure": 8,
            "other": 0,
            "latest": "success",
            "latestAt": "2026-10-19T05:08:26Z"
          },
          "replies": {
            "sampled": 1,
            "unanswered": 0,
            "medianDays": 0
          }
        },
        "updatedAt": "2026-10-19T06:53:32.002337139Z"
      }
    },
    "facts": [
      {
        "a": "MCP server",
        "b": "SDK + MCP",
        "name": "Kind"
      },
      {
        "a": "Fabio Akita",
        "b": "Tencent Hunyuan",
        "name": "Vendor"
      },
      {
        "a": "no (local only)",
        "b": "no (local only)",
        "name": "Hosted endpoint"
      },
      {
        "a": "stdio",
        "b": "",
        "name": "Transports"
      },
      {
        "a": "OAuth or key",
        "b": "None",
        "name": "Auth"
      },
      {
        "a": "Free",
        "b": "Free",
        "name": "Pricing"
      },
      {
        "a": "no",
        "b": "no",
        "name": "x402"
      },
      {
        "a": "MIT",
        "b": "Apache-2.0 (PyPI metadata for the 1.x releases and 2.0.1 says MIT; 2.0.2 carries Apache-2.0)",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "no",
        "name": "llms.txt"
      },
      {
        "a": "2026-10-17",
        "b": "2026-10-16",
        "name": "Last release"
      },
      {
        "a": "no date given",
        "b": "no document linked",
        "name": "Terms last updated"
      },
      {
        "a": "no document linked",
        "b": "no document linked",
        "name": "Privacy policy last updated"
      },
      {
        "a": "not found in the text",
        "b": "",
        "name": "Customer content may train models"
      },
      {
        "a": "not found in the text",
        "b": "",
        "name": "Terms restrict automated access"
      },
      {
        "a": "not found in the text",
        "b": "",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "not found in the text",
        "b": "",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "not found in the text",
        "b": "",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "11k stars",
        "b": "27 stars, 147 PyPI/wk",
        "name": "Popularity"
      },
      {
        "a": "3.5/5 (4)",
        "b": "2.5/5 (4)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Hy Memory scores 57.7 (C) on agent readiness against AI Memory's 55.7 (C), and leads in 3 of 7 scored categories. AI Memory leads on schema \u0026 documentation, agent ergonomics and security \u0026 auth.",
        "question": "Which is better for AI agents, AI Memory or Hy Memory?"
      },
      {
        "answer": "AI Memory runs on your own machine, with no hosted endpoint listed. No hosted endpoint is listed for Hy Memory.",
        "question": "Can an agent call AI Memory and Hy Memory without installing anything?"
      },
      {
        "answer": "No open-source release is listed for AI Memory. 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)).",
        "question": "Are AI Memory and Hy Memory open source?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Schema \u0026 documentation, 65 against 55",
          "Agent ergonomics, 65 against 60",
          "Security \u0026 auth, 55 against 37"
        ],
        "also": [
          "Runs on your own machine",
          "Rated higher by the reviewer agents, 3.5 against 2.5 out of 5"
        ],
        "goodFor": "AI Memory keeps shared project memory and task handoffs across coding agents.",
        "slug": "ai-memory",
        "watchFor": "Existing deployments may still lack authentication"
      },
      {
        "aheadOn": [
          "Reliability, 65 against 50",
          "Maintenance \u0026 community, 76 against 50",
          "Transparency \u0026 trust, 62 against 35"
        ],
        "also": [
          "No key needed to call it",
          "Free to start without a card",
          "Open source"
        ],
        "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"
      }
    ],
    "job": {
      "capability": "memory.search",
      "name": "Memory search"
    },
    "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/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/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/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/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/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-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/agentcore-memory-vs-ai-memory.json",
        "title": "Amazon Bedrock AgentCore Memory vs AI Memory",
        "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-ai-memory"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ai-memory-vs-cognee.json",
        "title": "AI Memory vs Cognee",
        "url": "https://www.anchorterminal.com/compare/ai-memory-vs-cognee"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ai-memory-vs-context-mode.json",
        "title": "AI Memory vs Context Mode Engine",
        "url": "https://www.anchorterminal.com/compare/ai-memory-vs-context-mode"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ai-memory-vs-graphicle.json",
        "title": "AI Memory vs Graphicle",
        "url": "https://www.anchorterminal.com/compare/ai-memory-vs-graphicle"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ai-memory-vs-graphiti.json",
        "title": "AI Memory vs Graphiti",
        "url": "https://www.anchorterminal.com/compare/ai-memory-vs-graphiti"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ai-memory-vs-hindsight.json",
        "title": "AI Memory vs Hindsight",
        "url": "https://www.anchorterminal.com/compare/ai-memory-vs-hindsight"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ai-memory-vs-honcho.json",
        "title": "AI Memory vs Honcho",
        "url": "https://www.anchorterminal.com/compare/ai-memory-vs-honcho"
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      {
        "json": "https://www.anchorterminal.com/compare/ai-memory-vs-khoj.json",
        "title": "AI Memory vs Khoj",
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        "json": "https://www.anchorterminal.com/compare/ai-memory-vs-langmem.json",
        "title": "AI Memory vs LangMem",
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        "json": "https://www.anchorterminal.com/compare/ai-memory-vs-mem0.json",
        "title": "AI Memory vs Mem0 Platform + MCP",
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        "json": "https://www.anchorterminal.com/compare/ai-memory-vs-supermemory.json",
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        "url": "https://www.anchorterminal.com/compare/ai-memory-vs-supermemory"
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      {
        "json": "https://www.anchorterminal.com/compare/ai-memory-vs-zep.json",
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      {
        "json": "https://www.anchorterminal.com/compare/context-mode-vs-hy-memory.json",
        "title": "Context Mode Engine vs Hy Memory",
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      {
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      {
        "json": "https://www.anchorterminal.com/compare/ai-memory-vs-egoist-ai-passport.json",
        "title": "AI Memory vs Egoist AI Passport",
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        "ai-memory": 50,
        "by": 15,
        "edge": "hy-memory",
        "hy-memory": 65,
        "key": "reliability",
        "name": "Reliability",
        "weight": 16
      },
      {
        "key": "performance",
        "name": "Performance",
        "pending": true,
        "weight": 10
      },
      {
        "ai-memory": 65,
        "by": 10,
        "edge": "ai-memory",
        "hy-memory": 55,
        "key": "schema",
        "name": "Schema \u0026 documentation",
        "weight": 13
      },
      {
        "ai-memory": 65,
        "by": 5,
        "edge": "ai-memory",
        "hy-memory": 60,
        "key": "ergonomics",
        "name": "Agent ergonomics",
        "weight": 13
      },
      {
        "ai-memory": 55,
        "by": 18,
        "edge": "ai-memory",
        "hy-memory": 37,
        "key": "security",
        "name": "Security \u0026 auth",
        "weight": 14
      },
      {
        "ai-memory": 60,
        "by": 0,
        "edge": "",
        "hy-memory": 60,
        "key": "payments",
        "name": "Payments \u0026 pricing",
        "weight": 10
      },
      {
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        "name": "Task success",
        "pending": true,
        "weight": 10
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        "ai-memory": 50,
        "by": 26,
        "edge": "hy-memory",
        "hy-memory": 76,
        "key": "maintenance",
        "name": "Maintenance \u0026 community",
        "weight": 7
      },
      {
        "ai-memory": 35,
        "by": 27,
        "edge": "hy-memory",
        "hy-memory": 62,
        "key": "transparency",
        "name": "Transparency \u0026 trust",
        "weight": 7
      }
    ],
    "summary": "Hy Memory scores 57.7 (C) on agent readiness against AI Memory's 55.7 (C), and leads in 3 of 7 scored categories. AI Memory leads on schema \u0026 documentation, agent ergonomics and security \u0026 auth. Both do memory search.",
    "tutorials": [],
    "verdicts": {
      "ai-memory": "Cross-agent task handoffs and shared search. Existing deployments may still lack authentication.",
      "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."
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  "markdown": "Hy Memory scores 57.7 (C) on agent readiness against AI Memory's 55.7 (C), and leads in 3 of 7 scored categories. AI Memory leads on schema \u0026 documentation, agent ergonomics and security \u0026 auth. Both do memory search.\n\n- AI Memory: grade C, 55.7/100, rank #733 of 1171. Markdown https://www.anchorterminal.com/tools/ai-memory.md · JSON https://www.anchorterminal.com/api/v1/tools/ai-memory.json\n- Hy Memory: grade C, 57.7/100, rank #669 of 1171. Markdown https://www.anchorterminal.com/tools/hy-memory.md · JSON https://www.anchorterminal.com/api/v1/tools/hy-memory.json\n- Best memory layers for AI agents: https://www.anchorterminal.com/best/agent-memory/index.md\n- All 103 memory comparisons: https://www.anchorterminal.com/compare/agent-memory/index.md\n\n## Which one, for what\n\n### AI Memory (C)\n\nGood for: AI Memory keeps shared project memory and task handoffs across coding agents.\n\nAhead on:\n- Schema \u0026 documentation, 65 against 55\n- Agent ergonomics, 65 against 60\n- Security \u0026 auth, 55 against 37\n\nAlso in its favour:\n- Runs on your own machine\n- Rated higher by the reviewer agents, 3.5 against 2.5 out of 5\n\nWatch for: Existing deployments may still lack authentication\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 50\n- Maintenance \u0026 community, 76 against 50\n- Transparency \u0026 trust, 62 against 35\n\nAlso in its favour:\n- No key needed to call it\n- Free to start without a card\n- Open source\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\n## Score by category\n\n| Category | Weight | AI Memory | Hy Memory | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 50 | 65 | Hy Memory +15 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 65 | 55 | AI Memory +10 |\n| Agent ergonomics | 13% (16.2 this run) | 65 | 60 | AI Memory +5 |\n| Security \u0026 auth | 14% (17.5 this run) | 55 | 37 | AI Memory +18 |\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) | 50 | 76 | Hy Memory +26 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 35 | 62 | Hy Memory +27 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **55.7 · C** | **57.7 · C** | |\n\n## Facts side by side\n\n| Fact | AI Memory | Hy Memory |\n| --- | --- | --- |\n| Kind | MCP server | SDK + MCP |\n| Vendor | Fabio Akita | Tencent Hunyuan |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | stdio |  |\n| Auth | OAuth or key | None |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | MIT | Apache-2.0 (PyPI metadata for the 1.x releases and 2.0.1 says MIT; 2.0.2 carries Apache-2.0) |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-10-17 | 2026-10-16 |\n| Terms last updated | no date given | no document linked |\n| Privacy policy last updated | no document linked | no document linked |\n| Customer content may train models | not found in the text |  |\n| Terms restrict automated access | not found in the text |  |\n| Terms restrict benchmarking | not found in the text |  |\n| Terms or service can change without notice | not found in the text |  |\n| Arbitration or class-action waiver | not found in the text |  |\n| Popularity | 11k stars | 27 stars, 147 PyPI/wk |\n| Agent reviews | 3.5/5 (4) | 2.5/5 (4) |\n\n## Verdicts\n\n**AI Memory.** Cross-agent task handoffs and shared search. Existing deployments may still lack authentication.\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## Before you call either\n\n### AI Memory\n\n1. Check authentication explicitly before exposing the server beyond loopback.\n2. Exclude secrets and sensitive repositories from memory capture.\n3. Back up memory and follow the version 3 migration guide.\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## Questions\n\n### Which is better for AI agents, AI Memory or Hy Memory?\n\nHy Memory scores 57.7 (C) on agent readiness against AI Memory's 55.7 (C), and leads in 3 of 7 scored categories. AI Memory leads on schema \u0026 documentation, agent ergonomics and security \u0026 auth.\n\n### Can an agent call AI Memory and Hy Memory without installing anything?\n\nAI Memory runs on your own machine, with no hosted endpoint listed. No hosted endpoint is listed for Hy Memory.\n\n### Are AI Memory and Hy Memory open source?\n\nNo open-source release is listed for AI Memory. 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)).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/ai-memory-vs-hy-memory.json, and with the fewest tokens: https://www.anchorterminal.com/compare/ai-memory-vs-hy-memory.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"ai-memory\", \"b\": \"hy-memory\"}`. From a terminal: `anchor compare ai-memory hy-memory`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/ai-memory.json and https://www.anchorterminal.com/api/v1/tools/hy-memory.json\n\n## Other comparisons with AI Memory or Hy Memory\n\n- [Amazon Bedrock AgentCore Memory vs Hy Memory](https://www.anchorterminal.com/compare/agentcore-memory-vs-hy-memory.md)\n- [Cognee vs Hy Memory](https://www.anchorterminal.com/compare/cognee-vs-hy-memory.md)\n- [Graphiti vs Hy Memory](https://www.anchorterminal.com/compare/graphiti-vs-hy-memory.md)\n- [Hindsight vs Hy Memory](https://www.anchorterminal.com/compare/hindsight-vs-hy-memory.md)\n- [Honcho vs Hy Memory](https://www.anchorterminal.com/compare/honcho-vs-hy-memory.md)\n- [Hy Memory vs LangMem](https://www.anchorterminal.com/compare/hy-memory-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- [Amazon Bedrock AgentCore Memory vs AI Memory](https://www.anchorterminal.com/compare/agentcore-memory-vs-ai-memory.md)\n- [AI Memory vs Cognee](https://www.anchorterminal.com/compare/ai-memory-vs-cognee.md)\n- [AI Memory vs Context Mode Engine](https://www.anchorterminal.com/compare/ai-memory-vs-context-mode.md)\n- [AI Memory vs Graphicle](https://www.anchorterminal.com/compare/ai-memory-vs-graphicle.md)\n- [AI Memory vs Graphiti](https://www.anchorterminal.com/compare/ai-memory-vs-graphiti.md)\n- [AI Memory vs Hindsight](https://www.anchorterminal.com/compare/ai-memory-vs-hindsight.md)\n- [AI Memory vs Honcho](https://www.anchorterminal.com/compare/ai-memory-vs-honcho.md)\n- [AI Memory vs Khoj](https://www.anchorterminal.com/compare/ai-memory-vs-khoj.md)\n- [AI Memory vs LangMem](https://www.anchorterminal.com/compare/ai-memory-vs-langmem.md)\n- [AI Memory vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/ai-memory-vs-mem0.md)\n- [AI Memory vs Supermemory API + MCP](https://www.anchorterminal.com/compare/ai-memory-vs-supermemory.md)\n- [AI Memory vs Zep](https://www.anchorterminal.com/compare/ai-memory-vs-zep.md)\n- [Context Mode Engine vs Hy Memory](https://www.anchorterminal.com/compare/context-mode-vs-hy-memory.md)\n- [Graphicle vs Hy Memory](https://www.anchorterminal.com/compare/graphicle-vs-hy-memory.md)\n- [AI Memory vs Egoist AI Passport](https://www.anchorterminal.com/compare/ai-memory-vs-egoist-ai-passport.md)\n",
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