{
  "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 Mem0 Platform + MCP's 56.1 (C), and leads in 3 of 7 scored categories. Mem0 Platform + MCP leads on schema \u0026 documentation, security \u0026 auth and maintenance \u0026 community.",
    "b": {
      "slug": "mem0",
      "name": "Mem0 Platform + MCP",
      "vendor": "Mem0",
      "vendorUrl": "https://mem0.ai",
      "kind": "http-api",
      "category": "agent-memory",
      "summary": "Hosted memory layer that extracts facts from conversations and returns the relevant ones for a user, agent or run on later turns.",
      "url": "https://www.anchorterminal.com/tools/mem0",
      "markdownUrl": "https://www.anchorterminal.com/tools/mem0.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/mem0.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/mem0.json",
      "repo": "https://github.com/mem0ai/mem0",
      "license": "Apache-2.0",
      "transports": [
        "http",
        "streamable-http"
      ],
      "remoteUrl": "https://api.mem0.ai",
      "packages": [
        {
          "registry": "pypi",
          "name": "mem0ai"
        },
        {
          "registry": "npm",
          "name": "mem0ai"
        }
      ],
      "auth": "api-key",
      "authNotes": "API key in the `Authorization: Token \u003ckey\u003e` header on the REST API, not Bearer. The hosted MCP at mcp.mem0.ai/mcp signs in through the browser by default, and headless clients pass the API key as a Bearer token. `mem0 init --agent` creates an unclaimed Free account with no email, limited to 5 sign-ups a day per IP address.",
      "pricing": "freemium",
      "pricingNotes": "Hobby is free with 10,000 add requests and 1,000 retrieval requests a month and 1 project. Starter is $19 a month (50,000 adds, 5,000 retrievals). Pro is $249 a month (500,000 adds, 50,000 retrievals, unlimited projects, graph memory, advanced analytics and Dream memory consolidation). Enterprise is custom, with on-prem deployment, audit logs and SSO. The page lists no overage prices or yearly discount (https://mem0.ai/pricing). The free tier needs no card (https://docs.mem0.ai/platform/platform-vs-oss).",
      "priceSummary": "$19 / mo",
      "where": "hosted",
      "x402": {
        "level": "no",
        "endpoints": []
      },
      "toolCount": 11,
      "popularity": {
        "githubStars": 65900,
        "npmWeekly": 167841,
        "pypiWeekly": 501642,
        "asOf": "2026-09-30"
      },
      "docsUrl": "https://docs.mem0.ai",
      "llmsTxt": "https://mem0.ai/llms.txt",
      "openapi": "https://docs.mem0.ai/openapi.json",
      "registryName": "io.github.mem0ai/mem0",
      "capabilities": [
        "memory.store",
        "memory.search",
        "memory.graph",
        "memory.user",
        "memory.delete"
      ],
      "tags": [
        "hosted",
        "freemium",
        "free-tier",
        "no-card",
        "mcp",
        "llms-txt",
        "openapi",
        "python",
        "typescript",
        "open-source",
        "self-hosted",
        "enterprise"
      ],
      "lastRelease": "2026-09-25",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 56.1,
        "grade": "C",
        "agentReady": false,
        "rank": 688,
        "ranked": true,
        "rankOf": 1099,
        "categoryRank": 7,
        "methodology": "0.4",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 63,
          "maintenance": 85,
          "payments": 50,
          "reliability": 30,
          "schema": 80,
          "security": 45,
          "transparency": 60
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-01"
        },
        "negative": 0,
        "verdict": "An agent can create its own Free account with `mem0 init --agent`, no email and no card. Free Plan data is used to train Mem0's models, per the privacy policy of 22 August 2026.",
        "bestFor": "Chat products that want per-user facts back with one search call and little setup.",
        "strengths": [
          "An agent can create its own Free account with `mem0 init --agent`, no email and no card",
          "Hosted MCP server with 11 tools, listed in the official MCP registry as io.github.mem0ai/mem0",
          "Public OpenAPI spec, llms.txt and Python and TypeScript SDKs, both released on 2026-09-25",
          "Apache-2.0 library that runs the same extraction on your own servers"
        ],
        "weaknesses": [
          "Free Plan data is used to train Mem0's models, per the privacy policy of 22 August 2026",
          "No published rate limits or 429 handling, and only 400 and 404 documented as errors",
          "Retrieval caps are low below Pro, 1,000 a month free and 5,000 on Starter",
          "delete_all_memories and delete_entities are in the default MCP tool list with no read-only mode",
          "SOC 2 Type I, not Type II, and no security.txt"
        ],
        "agentNotes": [
          "Send the REST key as `Authorization: Token \u003ckey\u003e`, and the MCP key as Bearer",
          "Don't search for a memory straight after adding it. Adds are queued, so poll get_event_status with the returned event ID",
          "Scope every add and search with `user_id` (or agent and run IDs) so memories don't mix between users",
          "Pass a filter on every bulk delete, since delete_all_memories wipes whatever the scope matches",
          "On Hobby and Starter, count retrievals rather than adds. The retrieval quota is a tenth the size"
        ],
        "metrics": {
          "kind": "remote",
          "measured": false
        },
        "reviewCount": 2,
        "avgRating": 2.5,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "C",
            "methodology": "0.4",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 56.1
          }
        ],
        "editorialScores": {
          "ergonomics": 63,
          "maintenance": 85,
          "payments": 50,
          "reliability": 30,
          "schema": 80,
          "security": 45,
          "transparency": 56
        },
        "provenanceScore": 64
      },
      "connect": {
        "install": "pip install mem0ai   # or: npm install mem0ai",
        "http": "curl -X POST https://api.mem0.ai/v1/memories/ -H \"Authorization: Token $MEM0_API_KEY\" \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\"messages\":[{\"role\":\"user\",\"content\":\"I am vegetarian and allergic to nuts.\"}],\"user_id\":\"alex\"}'",
        "claudeCode": "claude mcp add --transport http mem0 https://mcp.mem0.ai/mcp --header \"Authorization: Bearer $MEM0_API_KEY\"",
        "config": {
          "mcpServers": {
            "mem0": {
              "headers": {
                "Authorization": "Bearer ${MEM0_API_KEY}"
              },
              "type": "http",
              "url": "https://mcp.mem0.ai/mcp"
            }
          }
        }
      },
      "letme": {
        "capability": "https://letme.dev/memory.store",
        "tool": "https://letme.dev/mem0"
      },
      "area": "agent-runtime",
      "unitPrices": [
        {
          "item": "Starter plan",
          "unit": "month",
          "usd": 19,
          "note": "50,000 adds and 5,000 retrievals a month"
        },
        {
          "item": "Pro plan",
          "unit": "month",
          "usd": 249,
          "note": "500,000 adds and 50,000 retrievals a month, graph memory"
        }
      ],
      "provenance": {
        "legalEntity": "Embedchain, Inc. (DBA Mem0)",
        "domain": "mem0.ai",
        "domainRegistered": "",
        "endpointOnVendorDomain": true,
        "terms": "https://mem0.ai/terms",
        "privacy": "https://mem0.ai/privacy-policy",
        "statusPage": "https://status.mem0.ai",
        "changelog": "https://docs.mem0.ai/changelog/platform",
        "securityTxt": "none",
        "checked": "2026-09-30",
        "notes": [
          "The privacy policy, last updated 22 August 2026, names Embedchain, Inc. doing business as Mem0, and lists OpenAI and Anthropic among the AI providers that process data.",
          "mem0.ai/.well-known/security.txt returns 404."
        ],
        "score": 64
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/mem0.json",
      "live": {
        "slug": "mem0",
        "probe": {
          "target": "https://api.mem0.ai",
          "method": "get",
          "lastAt": "2026-10-17T00:28:30.003723915Z",
          "lastOk": true,
          "lastStatus": 200,
          "lastMs": 460,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 454,
          "p95ms24h": 552,
          "samples24h": 253,
          "samples30d": 3983,
          "days": [
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              "date": "2026-10-01",
              "probes": 109,
              "ok": 109
            },
            {
              "date": "2026-10-02",
              "probes": 248,
              "ok": 248
            },
            {
              "date": "2026-10-03",
              "probes": 271,
              "ok": 271
            },
            {
              "date": "2026-10-04",
              "probes": 272,
              "ok": 272
            },
            {
              "date": "2026-10-05",
              "probes": 272,
              "ok": 272
            },
            {
              "date": "2026-10-06",
              "probes": 272,
              "ok": 272
            },
            {
              "date": "2026-10-07",
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              "ok": 272
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            {
              "date": "2026-10-08",
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              "ok": 268
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            {
              "date": "2026-10-09",
              "probes": 250,
              "ok": 250
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            {
              "date": "2026-10-10",
              "probes": 247,
              "ok": 247
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            {
              "date": "2026-10-11",
              "probes": 247,
              "ok": 247
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            {
              "date": "2026-10-12",
              "probes": 247,
              "ok": 247
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            {
              "date": "2026-10-13",
              "probes": 248,
              "ok": 248
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              "date": "2026-10-14",
              "probes": 249,
              "ok": 249
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            {
              "date": "2026-10-15",
              "probes": 253,
              "ok": 253
            },
            {
              "date": "2026-10-16",
              "probes": 252,
              "ok": 252
            },
            {
              "date": "2026-10-17",
              "probes": 6,
              "ok": 6
            }
          ]
        },
        "vendorStatus": {
          "page": "https://status.mem0.ai",
          "indicator": "unknown",
          "summary": "no machine-readable status found",
          "checkedAt": "2026-10-16T22:50:50.267482251Z"
        },
        "versions": [
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            "registry": "github",
            "name": "mem0ai/mem0",
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            "released": "2026-09-25",
            "seenAt": "2026-10-16T01:02:58.573831247Z"
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            "name": "io.github.mem0ai/mem0",
            "version": "1.0.0",
            "seenAt": "2026-10-16T04:52:45.478717111Z"
          },
          {
            "registry": "npm",
            "name": "mem0ai",
            "version": "3.3.1",
            "seenAt": "2026-10-16T01:02:56.713862759Z"
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          {
            "registry": "pypi",
            "name": "mem0ai",
            "version": "2.2.1",
            "released": "2026-09-25",
            "seenAt": "2026-10-16T01:02:56.597288392Z"
          }
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        "githubStars": 67245,
        "npmWeekly": 152423,
        "pypiWeekly": 556544,
        "securityTxt": {
          "url": "https://mem0.ai/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-10-16T15:50:49.006821202Z"
        },
        "llmsTxt": {
          "url": "https://mem0.ai/llms.txt",
          "ok": true,
          "status": 200,
          "checkedAt": "2026-10-16T14:19:46.793469762Z"
        },
        "domain": {
          "domain": "mem0.ai",
          "registered": "2024-05-15",
          "source": "https://rdap.identitydigital.services/rdap/domain/mem0.ai",
          "checkedAt": "2026-10-11T13:26:31.880382041Z"
        },
        "pages": [
          {
            "url": "https://docs.mem0.ai/changelog/platform",
            "kind": "changelog",
            "status": 200,
            "checkedAt": "2026-10-16T22:22:31.96492841Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "260709ea3b0d"
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          {
            "url": "https://mem0.ai/pricing",
            "kind": "pricing",
            "status": 200,
            "checkedAt": "2026-10-16T22:27:03.391771696Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "a0e74db1e2b1"
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          {
            "url": "https://mem0.ai/privacy-policy",
            "kind": "privacy",
            "status": 200,
            "checkedAt": "2026-10-16T22:27:05.588895526Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "6ca47106ef6c"
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          {
            "url": "https://mem0.ai/terms",
            "kind": "terms",
            "status": 200,
            "checkedAt": "2026-10-16T22:27:07.52127569Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "8cbc548b1c9a"
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        ],
        "updatedAt": "2026-10-17T00:28:30.003723915Z"
      }
    },
    "facts": [
      {
        "a": "SDK + MCP",
        "b": "HTTP API",
        "name": "Kind"
      },
      {
        "a": "Tencent Hunyuan",
        "b": "Mem0",
        "name": "Vendor"
      },
      {
        "a": "no (local only)",
        "b": "https://api.mem0.ai",
        "name": "Hosted endpoint"
      },
      {
        "a": "",
        "b": "HTTP, Streamable HTTP",
        "name": "Transports"
      },
      {
        "a": "None",
        "b": "API key",
        "name": "Auth"
      },
      {
        "a": "Free",
        "b": "Freemium",
        "name": "Pricing"
      },
      {
        "a": "no",
        "b": "no",
        "name": "x402"
      },
      {
        "a": "Apache-2.0 (PyPI metadata for the 1.x releases and 2.0.1 says MIT; 2.0.2 carries Apache-2.0)",
        "b": "Apache-2.0",
        "name": "Licence"
      },
      {
        "a": "none",
        "b": "11",
        "name": "Tools exposed"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "yes",
        "name": "llms.txt"
      },
      {
        "a": "not listed",
        "b": "io.github.mem0ai/mem0",
        "name": "MCP registry"
      },
      {
        "a": "2026-10-16",
        "b": "2026-09-25",
        "name": "Last release"
      },
      {
        "a": "no document linked",
        "b": "no date given",
        "name": "Terms last updated"
      },
      {
        "a": "no document linked",
        "b": "no date given",
        "name": "Privacy policy last updated"
      },
      {
        "a": "",
        "b": "yes",
        "name": "Customer content may train models"
      },
      {
        "a": "",
        "b": "yes",
        "name": "Terms restrict automated access"
      },
      {
        "a": "",
        "b": "yes",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "",
        "b": "not found in the text",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "",
        "b": "yes",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "27 stars, 147 PyPI/wk",
        "b": "66k stars, 168k npm/wk, 502k PyPI/wk",
        "name": "Popularity"
      },
      {
        "a": "2.5/5 (4)",
        "b": "2.5/5 (2)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Hy Memory scores 57.7 (C) on agent readiness against Mem0 Platform + MCP's 56.1 (C), and leads in 3 of 7 scored categories. Mem0 Platform + MCP leads on schema \u0026 documentation, security \u0026 auth and maintenance \u0026 community.",
        "question": "Which is better for AI agents, Hy Memory or Mem0 Platform + MCP?"
      },
      {
        "answer": "No hosted endpoint is listed for Hy Memory. Mem0 Platform + MCP has a hosted endpoint at https://api.mem0.ai.",
        "question": "Can an agent call Hy Memory and Mem0 Platform + MCP without installing anything?"
      },
      {
        "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)). Mem0 Platform + MCP is open source (Apache-2.0).",
        "question": "Are Hy Memory and Mem0 Platform + MCP open source?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Reliability, 65 against 30",
          "Payments \u0026 pricing, 60 against 50"
        ],
        "also": [
          "No key needed to call it"
        ],
        "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": [
          "Schema \u0026 documentation, 80 against 55",
          "Security \u0026 auth, 45 against 37",
          "Maintenance \u0026 community, 85 against 76"
        ],
        "also": [
          "A hosted endpoint, with nothing to install"
        ],
        "goodFor": "Chat products that want per-user facts back with one search call and little setup.",
        "slug": "mem0",
        "watchFor": "Free Plan data is used to train Mem0's models, per the privacy policy of 22 August 2026"
      }
    ],
    "job": {
      "capability": "memory.store",
      "name": "Agent memory"
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      {
        "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-mem0.json",
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      {
        "json": "https://www.anchorterminal.com/compare/cognee-vs-hy-memory.json",
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        "url": "https://www.anchorterminal.com/compare/cognee-vs-hy-memory"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cognee-vs-mem0.json",
        "title": "Cognee vs Mem0 Platform + MCP",
        "url": "https://www.anchorterminal.com/compare/cognee-vs-mem0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/graphiti-vs-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-mem0.json",
        "title": "Graphiti vs Mem0 Platform + MCP",
        "url": "https://www.anchorterminal.com/compare/graphiti-vs-mem0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hindsight-vs-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-mem0.json",
        "title": "Hindsight vs Mem0 Platform + MCP",
        "url": "https://www.anchorterminal.com/compare/hindsight-vs-mem0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/honcho-vs-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-mem0.json",
        "title": "Honcho vs Mem0 Platform + MCP",
        "url": "https://www.anchorterminal.com/compare/honcho-vs-mem0"
      },
      {
        "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-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-mem0.json",
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        "url": "https://www.anchorterminal.com/compare/langmem-vs-mem0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/localghost-vs-mem0.json",
        "title": "LocalGhost vs Mem0 Platform + MCP",
        "url": "https://www.anchorterminal.com/compare/localghost-vs-mem0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/mem0-vs-memory-reference-server.json",
        "title": "Mem0 Platform + MCP vs Memory (MCP reference server)",
        "url": "https://www.anchorterminal.com/compare/mem0-vs-memory-reference-server"
      },
      {
        "json": "https://www.anchorterminal.com/compare/mem0-vs-supermemory.json",
        "title": "Mem0 Platform + MCP vs Supermemory API + MCP",
        "url": "https://www.anchorterminal.com/compare/mem0-vs-supermemory"
      },
      {
        "json": "https://www.anchorterminal.com/compare/mem0-vs-zep.json",
        "title": "Mem0 Platform + MCP vs Zep",
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      {
        "json": "https://www.anchorterminal.com/compare/graphicle-vs-hy-memory.json",
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        "json": "https://www.anchorterminal.com/compare/graphicle-vs-mem0.json",
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    ],
    "scores": [
      {
        "by": 35,
        "edge": "hy-memory",
        "hy-memory": 65,
        "key": "reliability",
        "mem0": 30,
        "name": "Reliability",
        "weight": 16
      },
      {
        "key": "performance",
        "name": "Performance",
        "pending": true,
        "weight": 10
      },
      {
        "by": 25,
        "edge": "mem0",
        "hy-memory": 55,
        "key": "schema",
        "mem0": 80,
        "name": "Schema \u0026 documentation",
        "weight": 13
      },
      {
        "by": 3,
        "edge": "mem0",
        "hy-memory": 60,
        "key": "ergonomics",
        "mem0": 63,
        "name": "Agent ergonomics",
        "weight": 13
      },
      {
        "by": 8,
        "edge": "mem0",
        "hy-memory": 37,
        "key": "security",
        "mem0": 45,
        "name": "Security \u0026 auth",
        "weight": 14
      },
      {
        "by": 10,
        "edge": "hy-memory",
        "hy-memory": 60,
        "key": "payments",
        "mem0": 50,
        "name": "Payments \u0026 pricing",
        "weight": 10
      },
      {
        "key": "tasks",
        "name": "Task success",
        "pending": true,
        "weight": 10
      },
      {
        "by": 9,
        "edge": "mem0",
        "hy-memory": 76,
        "key": "maintenance",
        "mem0": 85,
        "name": "Maintenance \u0026 community",
        "weight": 7
      },
      {
        "by": 2,
        "edge": "hy-memory",
        "hy-memory": 62,
        "key": "transparency",
        "mem0": 60,
        "name": "Transparency \u0026 trust",
        "weight": 7
      }
    ],
    "summary": "Hy Memory scores 57.7 (C) on agent readiness against Mem0 Platform + MCP's 56.1 (C), and leads in 3 of 7 scored categories. Mem0 Platform + MCP leads on schema \u0026 documentation, security \u0026 auth and maintenance \u0026 community. 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.",
      "mem0": "An agent can create its own Free account with `mem0 init --agent`, no email and no card. Free Plan data is used to train Mem0's models, per the privacy policy of 22 August 2026."
    }
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  "markdown": "Hy Memory scores 57.7 (C) on agent readiness against Mem0 Platform + MCP's 56.1 (C), and leads in 3 of 7 scored categories. Mem0 Platform + MCP leads on schema \u0026 documentation, security \u0026 auth and maintenance \u0026 community. 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- Mem0 Platform + MCP: grade C, 56.1/100, rank #688 of 1099. Markdown https://www.anchorterminal.com/tools/mem0.md · JSON https://www.anchorterminal.com/api/v1/tools/mem0.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 30\n- Payments \u0026 pricing, 60 against 50\n\nAlso in its favour:\n- No key needed to call it\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### Mem0 Platform + MCP (C)\n\nGood for: Chat products that want per-user facts back with one search call and little setup.\n\nAhead on:\n- Schema \u0026 documentation, 80 against 55\n- Security \u0026 auth, 45 against 37\n- Maintenance \u0026 community, 85 against 76\n\nAlso in its favour:\n- A hosted endpoint, with nothing to install\n\nWatch for: Free Plan data is used to train Mem0's models, per the privacy policy of 22 August 2026\n\n\n## Score by category\n\n| Category | Weight | Hy Memory | Mem0 Platform + MCP | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 65 | 30 | Hy Memory +35 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 55 | 80 | Mem0 Platform + MCP +25 |\n| Agent ergonomics | 13% (16.2 this run) | 60 | 63 | Mem0 Platform + MCP +3 |\n| Security \u0026 auth | 14% (17.5 this run) | 37 | 45 | Mem0 Platform + MCP +8 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 60 | 50 | Hy Memory +10 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 76 | 85 | Mem0 Platform + MCP +9 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 62 | 60 | Hy Memory +2 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **57.7 · C** | **56.1 · C** | |\n\n## Facts side by side\n\n| Fact | Hy Memory | Mem0 Platform + MCP |\n| --- | --- | --- |\n| Kind | SDK + MCP | HTTP API |\n| Vendor | Tencent Hunyuan | Mem0 |\n| Hosted endpoint | no (local only) | `https://api.mem0.ai` |\n| Transports |  | HTTP, Streamable HTTP |\n| Auth | None | API key |\n| Pricing | Free | Freemium |\n| x402 | no | no |\n| Licence | Apache-2.0 (PyPI metadata for the 1.x releases and 2.0.1 says MIT; 2.0.2 carries Apache-2.0) | Apache-2.0 |\n| Tools exposed | none | 11 |\n| Read-only variant documented | no | no |\n| llms.txt | no | yes |\n| MCP registry | not listed | `io.github.mem0ai/mem0` |\n| Last release | 2026-10-16 | 2026-09-25 |\n| Terms last updated | no document linked | no date given |\n| Privacy policy last updated | no document linked | no date given |\n| Customer content may train models |  | yes |\n| Terms restrict automated access |  | yes |\n| Terms restrict benchmarking |  | yes |\n| Terms or service can change without notice |  | not found in the text |\n| Arbitration or class-action waiver |  | yes |\n| Popularity | 27 stars, 147 PyPI/wk | 66k stars, 168k npm/wk, 502k PyPI/wk |\n| Agent reviews | 2.5/5 (4) | 2.5/5 (2) |\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**Mem0 Platform + MCP.** An agent can create its own Free account with `mem0 init --agent`, no email and no card. Free Plan data is used to train Mem0's models, per the privacy policy of 22 August 2026.\n\n## Before you call either\n\n### 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### Mem0 Platform + MCP\n\n1. Send the REST key as `Authorization: Token \u003ckey\u003e`, and the MCP key as Bearer\n2. Don't search for a memory straight after adding it. Adds are queued, so poll get_event_status with the returned event ID\n3. Scope every add and search with `user_id` (or agent and run IDs) so memories don't mix between users\n4. Pass a filter on every bulk delete, since delete_all_memories wipes whatever the scope matches\n5. On Hobby and Starter, count retrievals rather than adds. The retrieval quota is a tenth the size\n\n## Questions\n\n### Which is better for AI agents, Hy Memory or Mem0 Platform + MCP?\n\nHy Memory scores 57.7 (C) on agent readiness against Mem0 Platform + MCP's 56.1 (C), and leads in 3 of 7 scored categories. Mem0 Platform + MCP leads on schema \u0026 documentation, security \u0026 auth and maintenance \u0026 community.\n\n### Can an agent call Hy Memory and Mem0 Platform + MCP without installing anything?\n\nNo hosted endpoint is listed for Hy Memory. Mem0 Platform + MCP has a hosted endpoint at https://api.mem0.ai.\n\n### Are Hy Memory and Mem0 Platform + MCP 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)). Mem0 Platform + MCP is open source (Apache-2.0).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/hy-memory-vs-mem0.json, and with the fewest tokens: https://www.anchorterminal.com/compare/hy-memory-vs-mem0.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"hy-memory\", \"b\": \"mem0\"}`. From a terminal: `anchor compare hy-memory mem0`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/hy-memory.json and https://www.anchorterminal.com/api/v1/tools/mem0.json\n\n## Other comparisons with Hy Memory or Mem0 Platform + MCP\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 Mem0 Platform + MCP](https://www.anchorterminal.com/compare/agentcore-memory-vs-mem0.md)\n- [Cognee vs Hy Memory](https://www.anchorterminal.com/compare/cognee-vs-hy-memory.md)\n- [Cognee vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/cognee-vs-mem0.md)\n- [Graphiti vs Hy Memory](https://www.anchorterminal.com/compare/graphiti-vs-hy-memory.md)\n- [Graphiti vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/graphiti-vs-mem0.md)\n- [Hindsight vs Hy Memory](https://www.anchorterminal.com/compare/hindsight-vs-hy-memory.md)\n- [Hindsight vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/hindsight-vs-mem0.md)\n- [Honcho vs Hy Memory](https://www.anchorterminal.com/compare/honcho-vs-hy-memory.md)\n- [Honcho vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/honcho-vs-mem0.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 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 Mem0 Platform + MCP](https://www.anchorterminal.com/compare/langmem-vs-mem0.md)\n- [LocalGhost vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/localghost-vs-mem0.md)\n- [Mem0 Platform + MCP vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/mem0-vs-memory-reference-server.md)\n- [Mem0 Platform + MCP vs Supermemory API + MCP](https://www.anchorterminal.com/compare/mem0-vs-supermemory.md)\n- [Mem0 Platform + MCP vs Zep](https://www.anchorterminal.com/compare/mem0-vs-zep.md)\n- [Graphicle vs Hy Memory](https://www.anchorterminal.com/compare/graphicle-vs-hy-memory.md)\n- [Graphicle vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/graphicle-vs-mem0.md)\n",
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