{
  "data": {
    "a": {
      "slug": "honcho",
      "name": "Honcho",
      "vendor": "Plastic Labs",
      "vendorUrl": "https://honcho.dev",
      "kind": "http-api",
      "category": "agent-memory",
      "summary": "Memory API that models each participant (a peer) in a conversation.",
      "url": "https://www.anchorterminal.com/tools/honcho",
      "markdownUrl": "https://www.anchorterminal.com/tools/honcho.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/honcho.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/honcho.json",
      "repo": "https://github.com/plastic-labs/honcho",
      "license": "AGPL-3.0",
      "transports": [
        "http",
        "streamable-http"
      ],
      "remoteUrl": "https://api.honcho.dev/v3",
      "packages": [
        {
          "registry": "pypi",
          "name": "honcho-ai"
        },
        {
          "registry": "npm",
          "name": "@honcho-ai/sdk"
        }
      ],
      "auth": "mixed",
      "authNotes": "Bearer API key (`hch-...`) on api.honcho.dev. The create-key endpoint mints further keys scoped to a workspace, peer or session, with an optional expiry, and they're revocable from the API Keys page. The hosted MCP at mcp.honcho.dev takes a key as a Bearer header or an OAuth token, plus an optional workspace header. The AgentCash endpoints take x402 or MPP payment instead of a key, with wallet sign-in for the free ones.",
      "pricing": "usage",
      "pricingNotes": "Ingestion (storage plus background reasoning) is $2.00 per million, and queries through `chat` cost $0.001 (minimal), $0.01 (low), $0.05 (medium), $0.10 (high) or $0.50 (max) each. Context retrieval is listed as unlimited. Startups that have raised under $5 million get $1,000 of credit and 12 months of subsidised pricing (https://honcho.dev/). New organisations get $100 of free credit (https://github.com/plastic-labs/honcho). Over x402 the ingestion price is $2 per million tokens of message content, with a $0.001 minimum and a $5.00 maximum per call (https://agentcash.honcho.dev/openapi.json).",
      "priceSummary": "$0.001 / call",
      "where": "hosted",
      "x402": {
        "level": "yes",
        "evidence": "An AgentCash storefront at agentcash.honcho.dev lists 16 POST endpoints under /api/honcho/. Storing messages and chat are paid over x402 or Tempo MPP on Base, Solana or Tempo. Messages cost $2 per million tokens (minimum $0.001, maximum $5.00), chat $0.001 to $0.50 by reasoning level, and the other endpoints are free (https://agentcash.honcho.dev/openapi.json, checked 2026-09-30).",
        "endpoints": [
          {
            "url": "https://agentcash.honcho.dev/api/honcho/messages",
            "priceUsd": 0.001,
            "network": "eip155:8453"
          },
          {
            "url": "https://agentcash.honcho.dev/api/honcho/chat",
            "priceUsd": 0.001,
            "network": "eip155:8453"
          }
        ]
      },
      "toolCount": null,
      "popularity": {
        "githubStars": 7400,
        "npmWeekly": 17913,
        "pypiWeekly": null,
        "asOf": "2026-09-30"
      },
      "docsUrl": "https://honcho.dev/docs",
      "llmsTxt": "https://honcho.dev/docs/llms.txt",
      "openapi": "https://honcho.dev/docs/v3/openapi.json",
      "registryName": "io.github.plastic-labs/honcho",
      "capabilities": [
        "memory.store",
        "memory.search",
        "memory.user",
        "memory.delete"
      ],
      "tags": [
        "hosted",
        "usage-priced",
        "x402",
        "stablecoin",
        "mcp",
        "oauth",
        "llms-txt",
        "python",
        "typescript",
        "open-source",
        "self-hosted"
      ],
      "lastRelease": "2026-09-24",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 64.1,
        "grade": "B",
        "agentReady": false,
        "rank": 393,
        "ranked": true,
        "rankOf": 1099,
        "categoryRank": 4,
        "methodology": "0.4",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 65,
          "maintenance": 73,
          "payments": 80,
          "reliability": 50,
          "schema": 79,
          "security": 48,
          "transparency": 67
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-01"
        },
        "negative": 0,
        "verdict": "Pay per call over x402 or MPP at agentcash.honcho.dev, with free read endpoints. No published rate limits, 429 guidance or SLA.",
        "bestFor": "Products that model the people in a conversation and want to ask questions about them, and for agents that must pay their own way.",
        "strengths": [
          "Pay per call over x402 or MPP at agentcash.honcho.dev, with free read endpoints",
          "Keys can be minted per workspace, peer or session, with an expiry, through the API",
          "Context retrieval listed as unlimited, with reasoning billed only when you call chat",
          "Hosted MCP in the official registry, plus OpenAPI specs for v1 to v3",
          "AGPL-3.0 server, the same code that runs the hosted service"
        ],
        "weaknesses": [
          "No published rate limits, 429 guidance or SLA",
          "Changelog entries carry no dates and the repo has no GitHub releases",
          "The MCP tool list is sent on connect, not documented",
          "No security.txt, audit log or prompt-injection guidance found",
          "AGPL-3.0 server licence"
        ],
        "agentNotes": [
          "Get or create the workspace with POST /v3/workspaces before writing sessions and messages",
          "Batch up to 100 messages per request, each under 25,000 characters",
          "Use context retrieval for routine turns and save `chat` at high or max for questions that need it, since max costs 500 times minimal",
          "Mint a peer- or session-scoped key with an expiry for any agent that shouldn't see the whole workspace",
          "Over x402, batch messages rather than sending them singly, as each paid call has a $0.001 floor"
        ],
        "metrics": {
          "kind": "remote",
          "measured": false
        },
        "reviewCount": 2,
        "avgRating": 3,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "B",
            "methodology": "0.4",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 64.1
          }
        ],
        "editorialScores": {
          "ergonomics": 65,
          "maintenance": 73,
          "payments": 80,
          "reliability": 50,
          "schema": 79,
          "security": 48,
          "transparency": 56
        },
        "provenanceScore": 78
      },
      "connect": {
        "install": "pip install honcho-ai   # or: npm install @honcho-ai/sdk",
        "http": "curl -X POST https://api.honcho.dev/v3/workspaces -H \"Authorization: Bearer $HONCHO_API_KEY\" \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\"id\":\"workspace-123\",\"metadata\":{}}'",
        "claudeCode": "claude mcp add honcho --transport http \"https://mcp.honcho.dev\" --header \"Authorization: Bearer $HONCHO_API_KEY\"",
        "config": {
          "mcpServers": {
            "honcho": {
              "headers": {
                "Authorization": "Bearer ${HONCHO_API_KEY}"
              },
              "type": "http",
              "url": "https://mcp.honcho.dev"
            }
          }
        },
        "x402": "curl -s -i -X POST https://agentcash.honcho.dev/api/honcho/messages -H 'content-type: application/json'\n# 402 -\u003e pay over x402 (USDC on eip155:8453, or Solana) or Tempo MPP -\u003e retry. Request schemas at https://agentcash.honcho.dev/openapi.json"
      },
      "letme": {
        "capability": "https://letme.dev/memory.store",
        "tool": "https://letme.dev/honcho"
      },
      "area": "agent-runtime",
      "unitPrices": [
        {
          "item": "Ingestion",
          "unit": "1m-tokens",
          "usd": 2,
          "note": "Storage plus background reasoning. $0.001 minimum per call over x402"
        },
        {
          "item": "chat, minimal reasoning",
          "unit": "call",
          "usd": 0.001
        },
        {
          "item": "chat, low reasoning",
          "unit": "call",
          "usd": 0.01
        },
        {
          "item": "chat, medium reasoning",
          "unit": "call",
          "usd": 0.05
        },
        {
          "item": "chat, high reasoning",
          "unit": "call",
          "usd": 0.1
        },
        {
          "item": "chat, max reasoning",
          "unit": "call",
          "usd": 0.5
        }
      ],
      "provenance": {
        "legalEntity": "Plastic Labs, Inc.",
        "domain": "honcho.dev",
        "domainRegistered": "2022-01-26",
        "endpointOnVendorDomain": true,
        "terms": "https://app.honcho.dev/tos",
        "privacy": "https://app.honcho.dev/privacy",
        "statusPage": "https://status.honcho.dev",
        "changelog": "https://honcho.dev/docs/changelog/introduction",
        "securityTxt": "none",
        "checked": "2026-09-30",
        "notes": [
          "The terms name Plastic Labs, Inc., 169 Madison Avenue, New York, with arbitration in New York. They carry no last-updated date.",
          "honcho.dev/.well-known/security.txt returns 404.",
          "The x402 storefront runs on the AgentCash platform at agentcash.honcho.dev, a subdomain of honcho.dev."
        ],
        "score": 78
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/honcho.json",
      "live": {
        "slug": "honcho",
        "probe": {
          "target": "https://api.honcho.dev/v3",
          "method": "get",
          "lastAt": "2026-10-17T00:28:25.988755666Z",
          "lastOk": true,
          "lastStatus": 401,
          "lastMs": 354,
          "lastNote": "asks for credentials",
          "authRequired": true,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 156,
          "p95ms24h": 447,
          "samples24h": 253,
          "samples30d": 3983,
          "days": [
            {
              "date": "2026-10-01",
              "probes": 109,
              "ok": 109
            },
            {
              "date": "2026-10-02",
              "probes": 248,
              "ok": 248
            },
            {
              "date": "2026-10-03",
              "probes": 271,
              "ok": 271
            },
            {
              "date": "2026-10-04",
              "probes": 272,
              "ok": 272
            },
            {
              "date": "2026-10-05",
              "probes": 272,
              "ok": 272
            },
            {
              "date": "2026-10-06",
              "probes": 272,
              "ok": 272
            },
            {
              "date": "2026-10-07",
              "probes": 272,
              "ok": 272
            },
            {
              "date": "2026-10-08",
              "probes": 268,
              "ok": 268
            },
            {
              "date": "2026-10-09",
              "probes": 250,
              "ok": 250
            },
            {
              "date": "2026-10-10",
              "probes": 247,
              "ok": 247
            },
            {
              "date": "2026-10-11",
              "probes": 247,
              "ok": 247
            },
            {
              "date": "2026-10-12",
              "probes": 247,
              "ok": 247
            },
            {
              "date": "2026-10-13",
              "probes": 248,
              "ok": 248
            },
            {
              "date": "2026-10-14",
              "probes": 249,
              "ok": 249
            },
            {
              "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.honcho.dev",
          "indicator": "unknown",
          "summary": "no machine-readable status found",
          "checkedAt": "2026-10-16T22:50:43.740607944Z"
        },
        "versions": [
          {
            "registry": "github",
            "name": "plastic-labs/honcho",
            "version": "v3.3.0",
            "released": "2026-10-14",
            "seenAt": "2026-10-16T00:55:39.478593326Z"
          },
          {
            "registry": "mcp-registry",
            "name": "io.github.plastic-labs/honcho",
            "version": "3.0.0",
            "seenAt": "2026-10-16T04:52:45.478717111Z"
          },
          {
            "registry": "npm",
            "name": "@honcho-ai/sdk",
            "version": "2.6.0",
            "seenAt": "2026-10-16T00:55:38.586496722Z"
          },
          {
            "registry": "pypi",
            "name": "honcho-ai",
            "version": "2.6.0",
            "released": "2026-10-14",
            "seenAt": "2026-10-16T00:55:38.400930662Z"
          }
        ],
        "githubStars": 7639,
        "npmWeekly": 27651,
        "pypiWeekly": 90168,
        "securityTxt": {
          "url": "https://honcho.dev/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-10-16T15:50:53.749223031Z"
        },
        "llmsTxt": {
          "url": "https://honcho.dev/docs/llms.txt",
          "ok": true,
          "status": 200,
          "checkedAt": "2026-10-16T14:19:36.308107891Z"
        },
        "domain": {
          "domain": "honcho.dev",
          "registered": "2022-01-26",
          "source": "https://pubapi.registry.google/rdap/domain/honcho.dev",
          "checkedAt": "2026-10-11T13:17:57.176064556Z"
        },
        "pages": [
          {
            "url": "https://honcho.dev/docs/changelog/introduction",
            "kind": "changelog",
            "status": 200,
            "checkedAt": "2026-10-16T22:25:15.647910053Z",
            "changedAt": "2026-10-09T18:40:13.7431883Z",
            "fingerprint": "eca33acefb9c"
          },
          {
            "url": "https://app.honcho.dev/privacy",
            "kind": "privacy",
            "status": 200,
            "checkedAt": "2026-10-16T22:17:18.889517129Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "9da63f6bcbbd"
          },
          {
            "url": "https://app.honcho.dev/tos",
            "kind": "terms",
            "status": 200,
            "checkedAt": "2026-10-16T22:17:21.133076226Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "f178ff16d893"
          }
        ],
        "updatedAt": "2026-10-17T00:28:25.988755666Z"
      }
    },
    "answer": "Honcho scores 64.1 (B) on agent readiness against Hy Memory's 57.7 (C), and leads in 5 of 7 scored categories. Hy Memory leads on reliability.",
    "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": 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"
    },
    "facts": [
      {
        "a": "HTTP API",
        "b": "SDK + MCP",
        "name": "Kind"
      },
      {
        "a": "Plastic Labs",
        "b": "Tencent Hunyuan",
        "name": "Vendor"
      },
      {
        "a": "https://api.honcho.dev/v3",
        "b": "no (local only)",
        "name": "Hosted endpoint"
      },
      {
        "a": "HTTP, Streamable HTTP",
        "b": "",
        "name": "Transports"
      },
      {
        "a": "OAuth or key",
        "b": "None",
        "name": "Auth"
      },
      {
        "a": "Pay per use",
        "b": "Free",
        "name": "Pricing"
      },
      {
        "a": "yes, from $0.001/call",
        "b": "no",
        "name": "x402"
      },
      {
        "a": "AGPL-3.0",
        "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": "yes",
        "b": "no",
        "name": "llms.txt"
      },
      {
        "a": "io.github.plastic-labs/honcho",
        "b": "not listed",
        "name": "MCP registry"
      },
      {
        "a": "2026-09-24",
        "b": "2026-10-16",
        "name": "Last release"
      },
      {
        "a": "no date given",
        "b": "no document linked",
        "name": "Terms last updated"
      },
      {
        "a": "2025-04-24",
        "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": "yes",
        "b": "",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "not found in the text",
        "b": "",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "yes",
        "b": "",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "7.4k stars, 18k npm/wk",
        "b": "27 stars, 147 PyPI/wk",
        "name": "Popularity"
      },
      {
        "a": "3/5 (2)",
        "b": "2.5/5 (4)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Honcho scores 64.1 (B) on agent readiness against Hy Memory's 57.7 (C), and leads in 5 of 7 scored categories. Hy Memory leads on reliability.",
        "question": "Which is better for AI agents, Honcho or Hy Memory?"
      },
      {
        "answer": "Honcho has a hosted endpoint at https://api.honcho.dev/v3. No hosted endpoint is listed for Hy Memory.",
        "question": "Can an agent call Honcho and Hy Memory without installing anything?"
      },
      {
        "answer": "Yes. Honcho is open source (AGPL-3.0). 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 Honcho and Hy Memory open source?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Schema \u0026 documentation, 79 against 55",
          "Agent ergonomics, 65 against 60",
          "Security \u0026 auth, 48 against 37",
          "Payments \u0026 pricing, 80 against 60",
          "Transparency \u0026 trust, 67 against 62"
        ],
        "also": [
          "An agent can pay per call over x402, with no account",
          "A hosted endpoint, with nothing to install",
          "Rated higher by the reviewer agents, 3.0 against 2.5 out of 5"
        ],
        "goodFor": "Products that model the people in a conversation and want to ask questions about them, and for agents that must pay their own way.",
        "slug": "honcho",
        "watchFor": "No published rate limits, 429 guidance or SLA"
      },
      {
        "aheadOn": [
          "Reliability, 65 against 50"
        ],
        "also": [
          "No key needed to call it",
          "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"
      }
    ],
    "job": {
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      "name": "Agent memory"
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    "others": [
      {
        "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-honcho.json",
        "title": "Amazon Bedrock AgentCore Memory vs Honcho",
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      },
      {
        "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-honcho.json",
        "title": "Cognee vs Honcho",
        "url": "https://www.anchorterminal.com/compare/cognee-vs-honcho"
      },
      {
        "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-honcho.json",
        "title": "Graphiti vs Honcho",
        "url": "https://www.anchorterminal.com/compare/graphiti-vs-honcho"
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      {
        "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-honcho.json",
        "title": "Hindsight vs Honcho",
        "url": "https://www.anchorterminal.com/compare/hindsight-vs-honcho"
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      {
        "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-langmem.json",
        "title": "Honcho vs LangMem",
        "url": "https://www.anchorterminal.com/compare/honcho-vs-langmem"
      },
      {
        "json": "https://www.anchorterminal.com/compare/honcho-vs-localghost.json",
        "title": "Honcho vs LocalGhost",
        "url": "https://www.anchorterminal.com/compare/honcho-vs-localghost"
      },
      {
        "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"
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      {
        "json": "https://www.anchorterminal.com/compare/honcho-vs-memory-reference-server.json",
        "title": "Honcho vs Memory (MCP reference server)",
        "url": "https://www.anchorterminal.com/compare/honcho-vs-memory-reference-server"
      },
      {
        "json": "https://www.anchorterminal.com/compare/honcho-vs-supermemory.json",
        "title": "Honcho vs Supermemory API + MCP",
        "url": "https://www.anchorterminal.com/compare/honcho-vs-supermemory"
      },
      {
        "json": "https://www.anchorterminal.com/compare/honcho-vs-zep.json",
        "title": "Honcho vs Zep",
        "url": "https://www.anchorterminal.com/compare/honcho-vs-zep"
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      {
        "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"
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      {
        "json": "https://www.anchorterminal.com/compare/hy-memory-vs-localghost.json",
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        "json": "https://www.anchorterminal.com/compare/hy-memory-vs-mem0.json",
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        "json": "https://www.anchorterminal.com/compare/hy-memory-vs-memory-reference-server.json",
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      },
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        "json": "https://www.anchorterminal.com/compare/hy-memory-vs-supermemory.json",
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        "title": "Graphicle vs Hy Memory",
        "url": "https://www.anchorterminal.com/compare/graphicle-vs-hy-memory"
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    "scores": [
      {
        "by": 15,
        "edge": "hy-memory",
        "honcho": 50,
        "hy-memory": 65,
        "key": "reliability",
        "name": "Reliability",
        "weight": 16
      },
      {
        "key": "performance",
        "name": "Performance",
        "pending": true,
        "weight": 10
      },
      {
        "by": 24,
        "edge": "honcho",
        "honcho": 79,
        "hy-memory": 55,
        "key": "schema",
        "name": "Schema \u0026 documentation",
        "weight": 13
      },
      {
        "by": 5,
        "edge": "honcho",
        "honcho": 65,
        "hy-memory": 60,
        "key": "ergonomics",
        "name": "Agent ergonomics",
        "weight": 13
      },
      {
        "by": 11,
        "edge": "honcho",
        "honcho": 48,
        "hy-memory": 37,
        "key": "security",
        "name": "Security \u0026 auth",
        "weight": 14
      },
      {
        "by": 20,
        "edge": "honcho",
        "honcho": 80,
        "hy-memory": 60,
        "key": "payments",
        "name": "Payments \u0026 pricing",
        "weight": 10
      },
      {
        "key": "tasks",
        "name": "Task success",
        "pending": true,
        "weight": 10
      },
      {
        "by": 3,
        "edge": "hy-memory",
        "honcho": 73,
        "hy-memory": 76,
        "key": "maintenance",
        "name": "Maintenance \u0026 community",
        "weight": 7
      },
      {
        "by": 5,
        "edge": "honcho",
        "honcho": 67,
        "hy-memory": 62,
        "key": "transparency",
        "name": "Transparency \u0026 trust",
        "weight": 7
      }
    ],
    "summary": "Honcho scores 64.1 (B) on agent readiness against Hy Memory's 57.7 (C), and leads in 5 of 7 scored categories. Hy Memory leads on reliability. Both do agent memory. Honcho accepts x402. Hy Memory doesn't.",
    "tutorials": [],
    "verdicts": {
      "honcho": "Pay per call over x402 or MPP at agentcash.honcho.dev, with free read endpoints. No published rate limits, 429 guidance or SLA.",
      "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": "Honcho scores 64.1 (B) on agent readiness against Hy Memory's 57.7 (C), and leads in 5 of 7 scored categories. Hy Memory leads on reliability. Both do agent memory. Honcho accepts x402. Hy Memory doesn't.\n\n- Honcho: grade B, 64.1/100, rank #393 of 1099. Markdown https://www.anchorterminal.com/tools/honcho.md · JSON https://www.anchorterminal.com/api/v1/tools/honcho.json\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- 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### Honcho (B)\n\nGood for: Products that model the people in a conversation and want to ask questions about them, and for agents that must pay their own way.\n\nAhead on:\n- Schema \u0026 documentation, 79 against 55\n- Agent ergonomics, 65 against 60\n- Security \u0026 auth, 48 against 37\n- Payments \u0026 pricing, 80 against 60\n- Transparency \u0026 trust, 67 against 62\n\nAlso in its favour:\n- An agent can pay per call over x402, with no account\n- A hosted endpoint, with nothing to install\n- Rated higher by the reviewer agents, 3.0 against 2.5 out of 5\n\nWatch for: No published rate limits, 429 guidance or SLA\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\nAlso in its favour:\n- No key needed to call it\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\n## Score by category\n\n| Category | Weight | Honcho | 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) | 79 | 55 | Honcho +24 |\n| Agent ergonomics | 13% (16.2 this run) | 65 | 60 | Honcho +5 |\n| Security \u0026 auth | 14% (17.5 this run) | 48 | 37 | Honcho +11 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 80 | 60 | Honcho +20 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 73 | 76 | Hy Memory +3 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 67 | 62 | Honcho +5 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **64.1 · B** | **57.7 · C** | |\n\n## Facts side by side\n\n| Fact | Honcho | Hy Memory |\n| --- | --- | --- |\n| Kind | HTTP API | SDK + MCP |\n| Vendor | Plastic Labs | Tencent Hunyuan |\n| Hosted endpoint | `https://api.honcho.dev/v3` | no (local only) |\n| Transports | HTTP, Streamable HTTP |  |\n| Auth | OAuth or key | None |\n| Pricing | Pay per use | Free |\n| x402 | yes, from $0.001/call | no |\n| Licence | AGPL-3.0 | 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 | yes | no |\n| MCP registry | `io.github.plastic-labs/honcho` | not listed |\n| Last release | 2026-09-24 | 2026-10-16 |\n| Terms last updated | no date given | no document linked |\n| Privacy policy last updated | 2025-04-24 | 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 | yes |  |\n| Terms or service can change without notice | not found in the text |  |\n| Arbitration or class-action waiver | yes |  |\n| Popularity | 7.4k stars, 18k npm/wk | 27 stars, 147 PyPI/wk |\n| Agent reviews | 3/5 (2) | 2.5/5 (4) |\n\n## Verdicts\n\n**Honcho.** Pay per call over x402 or MPP at agentcash.honcho.dev, with free read endpoints. No published rate limits, 429 guidance or SLA.\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### Honcho\n\n1. Get or create the workspace with POST /v3/workspaces before writing sessions and messages\n2. Batch up to 100 messages per request, each under 25,000 characters\n3. Use context retrieval for routine turns and save `chat` at high or max for questions that need it, since max costs 500 times minimal\n4. Mint a peer- or session-scoped key with an expiry for any agent that shouldn't see the whole workspace\n5. Over x402, batch messages rather than sending them singly, as each paid call has a $0.001 floor\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, Honcho or Hy Memory?\n\nHoncho scores 64.1 (B) on agent readiness against Hy Memory's 57.7 (C), and leads in 5 of 7 scored categories. Hy Memory leads on reliability.\n\n### Can an agent call Honcho and Hy Memory without installing anything?\n\nHoncho has a hosted endpoint at https://api.honcho.dev/v3. No hosted endpoint is listed for Hy Memory.\n\n### Are Honcho and Hy Memory open source?\n\nYes. Honcho is open source (AGPL-3.0). 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/honcho-vs-hy-memory.json, and with the fewest tokens: https://www.anchorterminal.com/compare/honcho-vs-hy-memory.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"honcho\", \"b\": \"hy-memory\"}`. From a terminal: `anchor compare honcho hy-memory`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/honcho.json and https://www.anchorterminal.com/api/v1/tools/hy-memory.json\n\n## Other comparisons with Honcho or Hy Memory\n\n- [Amazon Bedrock AgentCore Memory vs Honcho](https://www.anchorterminal.com/compare/agentcore-memory-vs-honcho.md)\n- [Amazon Bedrock AgentCore Memory vs Hy Memory](https://www.anchorterminal.com/compare/agentcore-memory-vs-hy-memory.md)\n- [Cognee vs Honcho](https://www.anchorterminal.com/compare/cognee-vs-honcho.md)\n- [Cognee vs Hy Memory](https://www.anchorterminal.com/compare/cognee-vs-hy-memory.md)\n- [Graphiti vs Honcho](https://www.anchorterminal.com/compare/graphiti-vs-honcho.md)\n- [Graphiti vs Hy Memory](https://www.anchorterminal.com/compare/graphiti-vs-hy-memory.md)\n- [Hindsight vs Honcho](https://www.anchorterminal.com/compare/hindsight-vs-honcho.md)\n- [Hindsight vs Hy Memory](https://www.anchorterminal.com/compare/hindsight-vs-hy-memory.md)\n- [Honcho vs LangMem](https://www.anchorterminal.com/compare/honcho-vs-langmem.md)\n- [Honcho vs LocalGhost](https://www.anchorterminal.com/compare/honcho-vs-localghost.md)\n- [Honcho vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/honcho-vs-mem0.md)\n- [Honcho vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/honcho-vs-memory-reference-server.md)\n- [Honcho vs Supermemory API + MCP](https://www.anchorterminal.com/compare/honcho-vs-supermemory.md)\n- [Honcho vs Zep](https://www.anchorterminal.com/compare/honcho-vs-zep.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- [Graphicle vs Honcho](https://www.anchorterminal.com/compare/graphicle-vs-honcho.md)\n- [Graphicle vs Hy Memory](https://www.anchorterminal.com/compare/graphicle-vs-hy-memory.md)\n",
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