{
  "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": "AI Memory scores 55.7 (C) on agent readiness against Graphiti's 53.3 (D), and leads in 2 of 7 scored categories. Graphiti leads on schema \u0026 documentation, maintenance \u0026 community and transparency \u0026 trust.",
    "b": {
      "slug": "graphiti",
      "name": "Graphiti",
      "vendor": "Zep",
      "vendorUrl": "https://www.getzep.com",
      "kind": "framework",
      "category": "agent-memory",
      "summary": "Open-source Python framework from Zep that builds a temporal knowledge graph from chat messages, text and JSON.",
      "url": "https://www.anchorterminal.com/tools/graphiti",
      "markdownUrl": "https://www.anchorterminal.com/tools/graphiti.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/graphiti.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/graphiti.json",
      "repo": "https://github.com/getzep/graphiti",
      "license": "Apache-2.0",
      "transports": [
        "streamable-http",
        "stdio"
      ],
      "packages": [
        {
          "registry": "pypi",
          "name": "graphiti-core"
        }
      ],
      "auth": "none",
      "authNotes": "Runs on your own machine. You supply an LLM key (OPENAI_API_KEY by default) and database settings such as FALKORDB_URI or NEO4J_URI, NEO4J_USER and NEO4J_PASSWORD.",
      "pricing": "free",
      "pricingNotes": "Free under Apache-2.0. You pay for the LLM and embedding calls it makes on every ingest and for running the graph database (https://github.com/getzep/graphiti). Zep sells a hosted memory service from the same team (https://www.getzep.com/pricing/).",
      "priceSummary": "Free · OSS",
      "where": "library",
      "x402": {
        "level": "no",
        "endpoints": []
      },
      "toolCount": 13,
      "popularity": {
        "githubStars": 29000,
        "npmWeekly": null,
        "pypiWeekly": 151251,
        "asOf": "2026-09-30"
      },
      "docsUrl": "https://help.getzep.com/graphiti/getting-started/overview",
      "llmsTxt": "https://help.getzep.com/llms.txt",
      "capabilities": [
        "memory.store",
        "memory.search",
        "memory.graph",
        "memory.delete"
      ],
      "tags": [
        "framework",
        "open-source",
        "self-hosted",
        "local",
        "python",
        "mcp",
        "llms-txt"
      ],
      "lastRelease": "2026-09-08",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 53.3,
        "grade": "D",
        "agentReady": false,
        "rank": 804,
        "ranked": true,
        "rankOf": 1171,
        "categoryRank": 12,
        "methodology": "0.4",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 51,
          "maintenance": 65,
          "payments": 60,
          "reliability": 50,
          "schema": 71,
          "security": 23,
          "transparency": 71
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-01"
        },
        "negative": 0,
        "verdict": "Apache-2.0, with FalkorDB, Neo4j or Amazon Neptune as the store. Every add runs LLM extraction, so ingestion costs tokens and time.",
        "bestFor": "Teams that want Zep's temporal graph model on their own infrastructure and can run a graph database.",
        "strengths": [
          "Apache-2.0, with FalkorDB, Neo4j or Amazon Neptune as the store",
          "13-tool MCP server over streamable HTTP or stdio, with a Docker Compose file",
          "Works with OpenAI, Anthropic, Gemini, Groq or a local OpenAI-compatible model",
          "Telemetry documented, content-free by its own statement, and off with one environment variable",
          "Three PyPI releases between 27 July and 8 September 2026"
        ],
        "weaknesses": [
          "Every add runs LLM extraction, so ingestion costs tokens and time",
          "The MCP HTTP endpoint has no authentication, and no tool carries readOnlyHint or destructiveHint",
          "Still 0.x, and the last three PyPI releases have no GitHub release notes",
          "255 open issues, including a broken MCP Docker build reported in July 2026",
          "No official entry in the MCP registry"
        ],
        "agentNotes": [
          "Set OPENAI_API_KEY (or another provider's key) and MODEL_NAME before starting the MCP server",
          "Use search_memory_facts for facts and search_nodes for entities instead of reading whole episodes",
          "Never call clear_graph to fix one fact. Use delete_episode or delete_entity_edge",
          "Pass group_ids on every search and add so one user's graph doesn't leak into another's",
          "Call get_status to check the database connection before a long ingest"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 2,
        "avgRating": 2.5,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "D",
            "methodology": "0.4",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 53.3
          }
        ],
        "editorialScores": {
          "ergonomics": 51,
          "maintenance": 65,
          "payments": 60,
          "reliability": 50,
          "schema": 71,
          "security": 23,
          "transparency": 78
        },
        "provenanceScore": 63
      },
      "connect": {
        "install": "pip install graphiti-core   # or: pip install graphiti-core[falkordb]",
        "claudeCode": "claude mcp add --transport http graphiti http://localhost:8000/mcp/",
        "config": {
          "mcpServers": {
            "graphiti": {
              "type": "http",
              "url": "http://localhost:8000/mcp/"
            }
          }
        }
      },
      "letme": {
        "capability": "https://letme.dev/memory.store",
        "tool": "https://letme.dev/graphiti"
      },
      "sameCompany": [
        "zep"
      ],
      "area": "agent-runtime",
      "provenance": {
        "legalEntity": "Zep Software, Inc.",
        "domain": "getzep.com",
        "domainRegistered": "2023-05-08",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://github.com/getzep/graphiti/releases",
        "securityTxt": "none",
        "checked": "2026-09-30",
        "notes": [
          "A library and local server, so there's no hosted endpoint. Zep Software, Inc. owns the repository and publishes its docs on help.getzep.com."
        ],
        "score": 63
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/graphiti.json",
      "live": {
        "slug": "graphiti",
        "versions": [
          {
            "registry": "github",
            "name": "getzep/graphiti",
            "version": "v0.31.1",
            "released": "2026-10-15",
            "seenAt": "2026-10-19T03:53:12.478472872Z"
          },
          {
            "registry": "pypi",
            "name": "graphiti-core",
            "version": "0.31.1",
            "released": "2026-10-15",
            "seenAt": "2026-10-19T03:53:12.363121296Z"
          }
        ],
        "githubStars": 31996,
        "pypiWeekly": 197676,
        "securityTxt": {
          "url": "https://getzep.com/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-10-18T15:53:46.46816437Z"
        },
        "llmsTxt": {
          "url": "https://help.getzep.com/llms.txt",
          "ok": true,
          "status": 200,
          "checkedAt": "2026-10-18T14:25:09.157524876Z"
        },
        "domain": {
          "domain": "getzep.com",
          "registered": "2023-05-08",
          "source": "https://rdap.verisign.com/com/v1/domain/getzep.com",
          "checkedAt": "2026-10-18T13:46:01.289065168Z"
        },
        "pages": [
          {
            "url": "https://www.getzep.com/pricing/",
            "kind": "pricing",
            "status": 200,
            "checkedAt": "2026-10-18T23:43:56.414081358Z",
            "changedAt": "2026-10-03T15:38:25.165141175Z",
            "fingerprint": "6ec6dab9051f"
          }
        ],
        "github": {
          "repo": "getzep/graphiti",
          "checkedAt": "2026-10-19T06:12:33.220837154Z",
          "stars": 32006,
          "archived": false,
          "issuesEnabled": true,
          "pushedAt": "2026-10-19T00:11:23Z",
          "openIssues": 234,
          "openPRs": 256,
          "issuesOpened90d": 129,
          "issuesClosed90d": 163,
          "prsMerged90d": 65,
          "ci": {
            "branch": "main",
            "runs": 50,
            "success": 50,
            "failure": 0,
            "other": 0,
            "latest": "success",
            "latestAt": "2026-10-19T00:11:37Z"
          },
          "advisories": [
            {
              "ghsa": "GHSA-gg5m-55jj-8m5g",
              "cve": "CVE-2026-32247",
              "severity": "high",
              "published": "2026-03-11T17:50:34Z"
            }
          ],
          "replies": {
            "sampled": 25,
            "unanswered": 20,
            "medianDays": 0.1
          }
        },
        "updatedAt": "2026-10-19T06:12:33.220837154Z"
      }
    },
    "facts": [
      {
        "a": "MCP server",
        "b": "Agent framework",
        "name": "Kind"
      },
      {
        "a": "Fabio Akita",
        "b": "Zep",
        "name": "Vendor"
      },
      {
        "a": "no (local only)",
        "b": "no (local only)",
        "name": "Hosted endpoint"
      },
      {
        "a": "stdio",
        "b": "Streamable HTTP, stdio",
        "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",
        "name": "Licence"
      },
      {
        "a": "none",
        "b": "13",
        "name": "Tools exposed"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "yes",
        "name": "llms.txt"
      },
      {
        "a": "2026-10-17",
        "b": "2026-09-08",
        "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": "29k stars, 151k PyPI/wk",
        "name": "Popularity"
      },
      {
        "a": "3.5/5 (4)",
        "b": "2.5/5 (2)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "AI Memory scores 55.7 (C) on agent readiness against Graphiti's 53.3 (D), and leads in 2 of 7 scored categories. Graphiti leads on schema \u0026 documentation, maintenance \u0026 community and transparency \u0026 trust.",
        "question": "Which is better for AI agents, AI Memory or Graphiti?"
      },
      {
        "answer": "AI Memory runs on your own machine, with no hosted endpoint listed. Graphiti runs on your own machine, with no hosted endpoint listed.",
        "question": "Can an agent call AI Memory and Graphiti without installing anything?"
      },
      {
        "answer": "No open-source release is listed for AI Memory. Graphiti is open source (Apache-2.0).",
        "question": "Are AI Memory and Graphiti open source?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Agent ergonomics, 65 against 51",
          "Security \u0026 auth, 55 against 23"
        ],
        "also": [
          "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": [
          "Schema \u0026 documentation, 71 against 65",
          "Maintenance \u0026 community, 65 against 50",
          "Transparency \u0026 trust, 71 against 35"
        ],
        "also": [
          "No key needed to call it",
          "Open source"
        ],
        "goodFor": "Teams that want Zep's temporal graph model on their own infrastructure and can run a graph database.",
        "slug": "graphiti",
        "watchFor": "Every add runs LLM extraction, so ingestion costs tokens and time"
      }
    ],
    "job": {
      "capability": "memory.search",
      "name": "Memory search"
    },
    "others": [
      {
        "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-graphiti.json",
        "title": "Amazon Bedrock AgentCore Memory vs Graphiti",
        "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-graphiti"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cognee-vs-graphiti.json",
        "title": "Cognee vs Graphiti",
        "url": "https://www.anchorterminal.com/compare/cognee-vs-graphiti"
      },
      {
        "json": "https://www.anchorterminal.com/compare/graphiti-vs-hindsight.json",
        "title": "Graphiti vs Hindsight",
        "url": "https://www.anchorterminal.com/compare/graphiti-vs-hindsight"
      },
      {
        "json": "https://www.anchorterminal.com/compare/graphiti-vs-honcho.json",
        "title": "Graphiti vs Honcho",
        "url": "https://www.anchorterminal.com/compare/graphiti-vs-honcho"
      },
      {
        "json": "https://www.anchorterminal.com/compare/graphiti-vs-hy-memory.json",
        "title": "Graphiti vs Hy Memory",
        "url": "https://www.anchorterminal.com/compare/graphiti-vs-hy-memory"
      },
      {
        "json": "https://www.anchorterminal.com/compare/graphiti-vs-langmem.json",
        "title": "Graphiti vs LangMem",
        "url": "https://www.anchorterminal.com/compare/graphiti-vs-langmem"
      },
      {
        "json": "https://www.anchorterminal.com/compare/graphiti-vs-localghost.json",
        "title": "Graphiti vs LocalGhost",
        "url": "https://www.anchorterminal.com/compare/graphiti-vs-localghost"
      },
      {
        "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/graphiti-vs-memory-reference-server.json",
        "title": "Graphiti vs Memory (MCP reference server)",
        "url": "https://www.anchorterminal.com/compare/graphiti-vs-memory-reference-server"
      },
      {
        "json": "https://www.anchorterminal.com/compare/graphiti-vs-supermemory.json",
        "title": "Graphiti vs Supermemory API + MCP",
        "url": "https://www.anchorterminal.com/compare/graphiti-vs-supermemory"
      },
      {
        "json": "https://www.anchorterminal.com/compare/graphiti-vs-zep.json",
        "title": "Graphiti vs Zep",
        "url": "https://www.anchorterminal.com/compare/graphiti-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-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"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ai-memory-vs-hy-memory.json",
        "title": "AI Memory vs Hy Memory",
        "url": "https://www.anchorterminal.com/compare/ai-memory-vs-hy-memory"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ai-memory-vs-khoj.json",
        "title": "AI Memory vs Khoj",
        "url": "https://www.anchorterminal.com/compare/ai-memory-vs-khoj"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ai-memory-vs-langmem.json",
        "title": "AI Memory vs LangMem",
        "url": "https://www.anchorterminal.com/compare/ai-memory-vs-langmem"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ai-memory-vs-mem0.json",
        "title": "AI Memory vs Mem0 Platform + MCP",
        "url": "https://www.anchorterminal.com/compare/ai-memory-vs-mem0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ai-memory-vs-supermemory.json",
        "title": "AI Memory vs Supermemory API + MCP",
        "url": "https://www.anchorterminal.com/compare/ai-memory-vs-supermemory"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ai-memory-vs-zep.json",
        "title": "AI Memory vs Zep",
        "url": "https://www.anchorterminal.com/compare/ai-memory-vs-zep"
      },
      {
        "json": "https://www.anchorterminal.com/compare/context-mode-vs-graphiti.json",
        "title": "Context Mode Engine vs Graphiti",
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    "scores": [
      {
        "ai-memory": 50,
        "by": 0,
        "edge": "",
        "graphiti": 50,
        "key": "reliability",
        "name": "Reliability",
        "weight": 16
      },
      {
        "key": "performance",
        "name": "Performance",
        "pending": true,
        "weight": 10
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      {
        "ai-memory": 65,
        "by": 6,
        "edge": "graphiti",
        "graphiti": 71,
        "key": "schema",
        "name": "Schema \u0026 documentation",
        "weight": 13
      },
      {
        "ai-memory": 65,
        "by": 14,
        "edge": "ai-memory",
        "graphiti": 51,
        "key": "ergonomics",
        "name": "Agent ergonomics",
        "weight": 13
      },
      {
        "ai-memory": 55,
        "by": 32,
        "edge": "ai-memory",
        "graphiti": 23,
        "key": "security",
        "name": "Security \u0026 auth",
        "weight": 14
      },
      {
        "ai-memory": 60,
        "by": 0,
        "edge": "",
        "graphiti": 60,
        "key": "payments",
        "name": "Payments \u0026 pricing",
        "weight": 10
      },
      {
        "key": "tasks",
        "name": "Task success",
        "pending": true,
        "weight": 10
      },
      {
        "ai-memory": 50,
        "by": 15,
        "edge": "graphiti",
        "graphiti": 65,
        "key": "maintenance",
        "name": "Maintenance \u0026 community",
        "weight": 7
      },
      {
        "ai-memory": 35,
        "by": 36,
        "edge": "graphiti",
        "graphiti": 71,
        "key": "transparency",
        "name": "Transparency \u0026 trust",
        "weight": 7
      }
    ],
    "summary": "AI Memory scores 55.7 (C) on agent readiness against Graphiti's 53.3 (D), and leads in 2 of 7 scored categories. Graphiti leads on schema \u0026 documentation, maintenance \u0026 community and transparency \u0026 trust. Both do memory search.",
    "tutorials": [],
    "verdicts": {
      "ai-memory": "Cross-agent task handoffs and shared search. Existing deployments may still lack authentication.",
      "graphiti": "Apache-2.0, with FalkorDB, Neo4j or Amazon Neptune as the store. Every add runs LLM extraction, so ingestion costs tokens and time."
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  "markdown": "AI Memory scores 55.7 (C) on agent readiness against Graphiti's 53.3 (D), and leads in 2 of 7 scored categories. Graphiti leads on schema \u0026 documentation, maintenance \u0026 community and transparency \u0026 trust. 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- Graphiti: grade D, 53.3/100, rank #804 of 1171. Markdown https://www.anchorterminal.com/tools/graphiti.md · JSON https://www.anchorterminal.com/api/v1/tools/graphiti.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- Agent ergonomics, 65 against 51\n- Security \u0026 auth, 55 against 23\n\nAlso in its favour:\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### Graphiti (D)\n\nGood for: Teams that want Zep's temporal graph model on their own infrastructure and can run a graph database.\n\nAhead on:\n- Schema \u0026 documentation, 71 against 65\n- Maintenance \u0026 community, 65 against 50\n- Transparency \u0026 trust, 71 against 35\n\nAlso in its favour:\n- No key needed to call it\n- Open source\n\nWatch for: Every add runs LLM extraction, so ingestion costs tokens and time\n\n\n## Score by category\n\n| Category | Weight | AI Memory | Graphiti | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 50 | 50 | even |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 65 | 71 | Graphiti +6 |\n| Agent ergonomics | 13% (16.2 this run) | 65 | 51 | AI Memory +14 |\n| Security \u0026 auth | 14% (17.5 this run) | 55 | 23 | AI Memory +32 |\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 | 65 | Graphiti +15 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 35 | 71 | Graphiti +36 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **55.7 · C** | **53.3 · D** | |\n\n## Facts side by side\n\n| Fact | AI Memory | Graphiti |\n| --- | --- | --- |\n| Kind | MCP server | Agent framework |\n| Vendor | Fabio Akita | Zep |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | stdio | Streamable HTTP, stdio |\n| Auth | OAuth or key | None |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | MIT | Apache-2.0 |\n| Tools exposed | none | 13 |\n| Read-only variant documented | no | no |\n| llms.txt | no | yes |\n| Last release | 2026-10-17 | 2026-09-08 |\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 | 29k stars, 151k PyPI/wk |\n| Agent reviews | 3.5/5 (4) | 2.5/5 (2) |\n\n## Verdicts\n\n**AI Memory.** Cross-agent task handoffs and shared search. Existing deployments may still lack authentication.\n\n**Graphiti.** Apache-2.0, with FalkorDB, Neo4j or Amazon Neptune as the store. Every add runs LLM extraction, so ingestion costs tokens and time.\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### Graphiti\n\n1. Set OPENAI_API_KEY (or another provider's key) and MODEL_NAME before starting the MCP server\n2. Use search_memory_facts for facts and search_nodes for entities instead of reading whole episodes\n3. Never call clear_graph to fix one fact. Use delete_episode or delete_entity_edge\n4. Pass group_ids on every search and add so one user's graph doesn't leak into another's\n5. Call get_status to check the database connection before a long ingest\n\n## Questions\n\n### Which is better for AI agents, AI Memory or Graphiti?\n\nAI Memory scores 55.7 (C) on agent readiness against Graphiti's 53.3 (D), and leads in 2 of 7 scored categories. Graphiti leads on schema \u0026 documentation, maintenance \u0026 community and transparency \u0026 trust.\n\n### Can an agent call AI Memory and Graphiti without installing anything?\n\nAI Memory runs on your own machine, with no hosted endpoint listed. Graphiti runs on your own machine, with no hosted endpoint listed.\n\n### Are AI Memory and Graphiti open source?\n\nNo open-source release is listed for AI Memory. Graphiti is open source (Apache-2.0).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/ai-memory-vs-graphiti.json, and with the fewest tokens: https://www.anchorterminal.com/compare/ai-memory-vs-graphiti.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"ai-memory\", \"b\": \"graphiti\"}`. From a terminal: `anchor compare ai-memory graphiti`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/ai-memory.json and https://www.anchorterminal.com/api/v1/tools/graphiti.json\n\n## Other comparisons with AI Memory or Graphiti\n\n- [Amazon Bedrock AgentCore Memory vs Graphiti](https://www.anchorterminal.com/compare/agentcore-memory-vs-graphiti.md)\n- [Cognee vs Graphiti](https://www.anchorterminal.com/compare/cognee-vs-graphiti.md)\n- [Graphiti vs Hindsight](https://www.anchorterminal.com/compare/graphiti-vs-hindsight.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- [Graphiti vs LangMem](https://www.anchorterminal.com/compare/graphiti-vs-langmem.md)\n- [Graphiti vs LocalGhost](https://www.anchorterminal.com/compare/graphiti-vs-localghost.md)\n- [Graphiti vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/graphiti-vs-mem0.md)\n- [Graphiti vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/graphiti-vs-memory-reference-server.md)\n- [Graphiti vs Supermemory API + MCP](https://www.anchorterminal.com/compare/graphiti-vs-supermemory.md)\n- [Graphiti vs Zep](https://www.anchorterminal.com/compare/graphiti-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 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 Hy Memory](https://www.anchorterminal.com/compare/ai-memory-vs-hy-memory.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 Graphiti](https://www.anchorterminal.com/compare/context-mode-vs-graphiti.md)\n- [Graphicle vs Graphiti](https://www.anchorterminal.com/compare/graphicle-vs-graphiti.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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