{
  "data": {
    "a": {
      "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": 333,
        "ranked": true,
        "rankOf": 452,
        "categoryRank": 6,
        "methodology": "0.3",
        "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.",
        "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": "0.3",
            "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": "v0.30.2",
            "released": "2026-09-08",
            "seenAt": "2026-10-04T16:29:13.398654956Z"
          },
          {
            "registry": "pypi",
            "name": "graphiti-core",
            "version": "0.30.2",
            "released": "2026-09-08",
            "seenAt": "2026-10-04T16:29:13.214213248Z"
          }
        ],
        "githubStars": 31430,
        "pypiWeekly": 142231,
        "securityTxt": {
          "url": "https://getzep.com/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-10-04T15:15:52.364915515Z"
        },
        "llmsTxt": {
          "url": "https://help.getzep.com/llms.txt",
          "ok": true,
          "status": 200,
          "checkedAt": "2026-10-04T15:17:51.568653025Z"
        },
        "domain": {
          "domain": "getzep.com",
          "registered": "2023-05-08",
          "source": "https://rdap.verisign.com/com/v1/domain/getzep.com",
          "checkedAt": "2026-10-04T13:03:48.930668589Z"
        },
        "pages": [
          {
            "url": "https://www.getzep.com/pricing/",
            "kind": "pricing",
            "status": 200,
            "checkedAt": "2026-10-04T15:50:33.53600163Z",
            "changedAt": "2026-10-03T15:38:25.165141175Z",
            "fingerprint": "6ec6dab9051f"
          }
        ],
        "updatedAt": "2026-10-04T16:29:13.398654956Z"
      }
    },
    "b": {
      "slug": "hindsight",
      "name": "Hindsight",
      "vendor": "Vectorize",
      "vendorUrl": "https://hindsight.vectorize.io",
      "kind": "http-api",
      "category": "agent-memory",
      "summary": "Memory engine for storing and retrieving information used by agents.",
      "url": "https://www.anchorterminal.com/tools/hindsight",
      "markdownUrl": "https://www.anchorterminal.com/tools/hindsight.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/hindsight.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/hindsight.json",
      "repo": "https://github.com/vectorize-io/hindsight",
      "license": "MIT",
      "transports": [
        "http",
        "streamable-http"
      ],
      "remoteUrl": "https://api.hindsight.vectorize.io",
      "packages": [
        {
          "registry": "pypi",
          "name": "hindsight-client"
        },
        {
          "registry": "npm",
          "name": "@vectorize-io/hindsight-client"
        },
        {
          "registry": "pypi",
          "name": "hindsight-api"
        }
      ],
      "auth": "mixed",
      "authNotes": "Bearer API key on api.hindsight.vectorize.io. Keys can be restricted to named banks and set to expire after an hour to a year, and revoking a parent key revokes its child keys. The hosted MCP uses OAuth with PKCE (RFC 9728), or the same key as a Bearer header. A self-hosted server exposes MCP at /mcp/{bank_id}/ on port 8888.",
      "pricing": "usage",
      "pricingNotes": "Hindsight Cloud is pay as you go, with no monthly fee or seat price. Retain $10.00 per million tokens, recall $0.75 per million, reflect $0.05 a call, Iris Extract $7.50 per million, mental model retrieval $0.25 per million, mental model refresh $0.05 a call, storage $0.25 per million tokens a month. New accounts get free credits, amount not stated. Enterprise adds dedicated infrastructure and up to a 99.95 per cent uptime SLA (https://vectorize.io/pricing). Credit is bought in amounts from $5 to $1,000, and calls return 402 once the balance is empty (https://docs.hindsight.vectorize.io/billing/). Self-hosting is free under MIT.",
      "priceSummary": "$0.05 / call",
      "where": "hosted",
      "x402": {
        "level": "no",
        "endpoints": []
      },
      "toolCount": 27,
      "popularity": {
        "githubStars": 43400,
        "npmWeekly": 44381,
        "pypiWeekly": 227251,
        "asOf": "2026-09-30"
      },
      "docsUrl": "https://docs.hindsight.vectorize.io",
      "openapi": "https://hindsight.vectorize.io/openapi.json",
      "capabilities": [
        "memory.store",
        "memory.search",
        "memory.delete"
      ],
      "tags": [
        "hosted",
        "usage-priced",
        "mcp",
        "oauth",
        "openapi",
        "python",
        "typescript",
        "open-source",
        "self-hosted",
        "enterprise"
      ],
      "lastRelease": "2026-09-29",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 50.4,
        "grade": "D",
        "agentReady": false,
        "rank": 359,
        "ranked": true,
        "rankOf": 452,
        "categoryRank": 7,
        "methodology": "0.3",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 57,
          "maintenance": 80,
          "payments": 30,
          "reliability": 25,
          "schema": 68,
          "security": 58,
          "transparency": 48
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-01"
        },
        "negative": 0,
        "verdict": "API keys support bank-level restrictions, expiry and child-key revocation. Retain ingestion costs $10 per million tokens.",
        "strengths": [
          "Keys restricted to named banks, with expiry from an hour to a year and child-key revocation",
          "`Memory Defense` screens every retain, with regex redaction even in the open-source server",
          "Published per-token and per-call Cloud prices, with no monthly fee, and a published 99.9 per cent SLA",
          "MIT server in one Docker image with an MCP endpoint per bank",
          "Eight PyPI releases between 22 July and 29 September 2026"
        ],
        "weaknesses": [
          "Retain at $10 per million tokens is the priciest ingestion in this category",
          "27 MCP tools per bank, with no subset or read-only option",
          "No status page, no published rate limits and no llms.txt",
          "Prompt-injection blocking and audit trails are Enterprise only",
          "Free credit amount not published"
        ],
        "agentNotes": [
          "Scope the MCP URL to one bank (/mcp/{bank}/) so every call lands in the right memory and three bank-admin tools drop out",
          "Use recall for lookups and keep reflect ($0.05 a call) for questions that need reasoning",
          "Pass `async: true` on large retains so the call returns before extraction finishes",
          "Treat HTTP 402 as out of credit and 403 as a key that can't reach that bank"
        ],
        "metrics": {
          "kind": "remote",
          "measured": false
        },
        "reviewCount": 2,
        "avgRating": 3,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "D",
            "methodology": "0.3",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 50.4
          }
        ],
        "editorialScores": {
          "ergonomics": 57,
          "maintenance": 80,
          "payments": 30,
          "reliability": 25,
          "schema": 68,
          "security": 58,
          "transparency": 30
        },
        "provenanceScore": 65
      },
      "connect": {
        "install": "pip install hindsight-client   # or: npm install @vectorize-io/hindsight-client",
        "http": "curl -s \"https://api.hindsight.vectorize.io/v1/default/banks/my-bank/memories/list\" -H \"Authorization: Bearer $HINDSIGHT_API_KEY\"",
        "claudeCode": "claude mcp add --transport http hindsight https://api.hindsight.vectorize.io/mcp/my-bank/",
        "config": {
          "mcpServers": {
            "hindsight": {
              "headers": {
                "Authorization": "Bearer ${HINDSIGHT_API_KEY}"
              },
              "type": "http",
              "url": "https://api.hindsight.vectorize.io/mcp/my-bank/"
            }
          }
        }
      },
      "letme": {
        "capability": "https://letme.dev/memory.store",
        "tool": "https://letme.dev/hindsight"
      },
      "area": "agent-runtime",
      "unitPrices": [
        {
          "item": "Retain",
          "unit": "1m-tokens",
          "usd": 10,
          "note": "input tokens"
        },
        {
          "item": "Recall",
          "unit": "1m-tokens",
          "usd": 0.75,
          "note": "output tokens"
        },
        {
          "item": "Reflect",
          "unit": "call",
          "usd": 0.05
        },
        {
          "item": "Iris Extract",
          "unit": "1m-tokens",
          "usd": 7.5
        },
        {
          "item": "Mental model refresh",
          "unit": "call",
          "usd": 0.05
        },
        {
          "item": "Storage",
          "unit": "1m-tokens",
          "usd": 0.25,
          "note": "per million tokens stored, per month"
        }
      ],
      "provenance": {
        "legalEntity": "Vectorize, Inc.",
        "domain": "vectorize.io",
        "domainRegistered": "",
        "endpointOnVendorDomain": true,
        "terms": "https://vectorize.io/terms",
        "privacy": "https://vectorize.io/privacy",
        "statusPage": "",
        "changelog": "https://docs.hindsight.vectorize.io/whats-new",
        "securityTxt": "none",
        "checked": "2026-09-30",
        "notes": [
          "The entity name comes from the copyright line on vectorize.io. The privacy policy is embedded from Termly and gives no address.",
          "vectorize.io/.well-known/security.txt returns 404, and we found no status page."
        ],
        "score": 65
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/hindsight.json",
      "live": {
        "slug": "hindsight",
        "probe": {
          "target": "https://api.hindsight.vectorize.io",
          "method": "get",
          "lastAt": "2026-10-05T01:43:38.512323289Z",
          "lastOk": true,
          "lastStatus": 404,
          "lastMs": 393,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 132,
          "p95ms24h": 396,
          "samples24h": 272,
          "samples30d": 920,
          "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": 20,
              "ok": 20
            }
          ]
        },
        "versions": [
          {
            "registry": "github",
            "name": "vectorize-io/hindsight",
            "version": "v0.10.2",
            "released": "2026-09-29",
            "seenAt": "2026-10-04T16:29:39.70608693Z"
          },
          {
            "registry": "npm",
            "name": "@vectorize-io/hindsight-client",
            "version": "0.10.2",
            "seenAt": "2026-10-04T16:29:37.810729722Z"
          },
          {
            "registry": "pypi",
            "name": "hindsight-api",
            "version": "0.10.2",
            "released": "2026-09-29",
            "seenAt": "2026-10-04T16:29:38.662862892Z"
          },
          {
            "registry": "pypi",
            "name": "hindsight-client",
            "version": "0.10.2",
            "released": "2026-09-29",
            "seenAt": "2026-10-04T16:29:37.622434193Z"
          }
        ],
        "githubStars": 45387,
        "npmWeekly": 65833,
        "pypiWeekly": 225330,
        "securityTxt": {
          "url": "https://vectorize.io/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-10-04T15:15:46.852372513Z"
        },
        "domain": {
          "domain": "vectorize.io",
          "checkedAt": "2026-10-04T13:05:24.522601574Z"
        },
        "pages": [
          {
            "url": "https://docs.hindsight.vectorize.io/whats-new",
            "kind": "changelog",
            "status": 304,
            "checkedAt": "2026-10-04T15:43:40.455785234Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "4b4e1a42fe21"
          },
          {
            "url": "https://vectorize.io/pricing",
            "kind": "pricing",
            "status": 304,
            "checkedAt": "2026-10-04T15:48:41.9940699Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "8914c2c291ed"
          },
          {
            "url": "https://vectorize.io/privacy",
            "kind": "privacy",
            "status": 304,
            "checkedAt": "2026-10-04T15:48:44.199762911Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "0b650c200752"
          },
          {
            "url": "https://vectorize.io/terms",
            "kind": "terms",
            "status": 304,
            "checkedAt": "2026-10-04T15:48:46.160685664Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "e508ab007e9c"
          }
        ],
        "updatedAt": "2026-10-05T01:43:38.512323289Z"
      }
    },
    "summary": "Graphiti has a score of 53.3 (D) against Hindsight's 50.4 (D). Both do memory store. The largest gap is security \u0026 auth, 35 points."
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/graphiti-vs-hindsight",
    "json": "https://www.anchorterminal.com/compare/graphiti-vs-hindsight.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/graphiti-vs-hindsight.md",
    "slim": "https://www.anchorterminal.com/compare/graphiti-vs-hindsight.min.md"
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  "markdown": "Graphiti has a score of 53.3 (D) against Hindsight's 50.4 (D). Both do memory store. The largest gap is security \u0026 auth, 35 points.\n\n- Graphiti: grade D, 53.3/100, rank #333 of 452. Markdown https://www.anchorterminal.com/tools/graphiti.md · JSON https://www.anchorterminal.com/api/v1/tools/graphiti.json\n- Hindsight: grade D, 50.4/100, rank #359 of 452. Markdown https://www.anchorterminal.com/tools/hindsight.md · JSON https://www.anchorterminal.com/api/v1/tools/hindsight.json\n\n## Which one, for what\n\nPick Graphiti for reliability (+25), payments \u0026 pricing (+30), transparency \u0026 trust (+23).\n\nPick Hindsight for agent ergonomics (+6), security \u0026 auth (+35), maintenance \u0026 community (+15).\n\n## Score by category\n\n| Category | Weight | Graphiti | Hindsight | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 50 | 25 | Graphiti +25 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 71 | 68 | Graphiti +3 |\n| Agent ergonomics | 13% (16.2 this run) | 51 | 57 | Hindsight +6 |\n| Security \u0026 auth | 14% (17.5 this run) | 23 | 58 | Hindsight +35 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 60 | 30 | Graphiti +30 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 65 | 80 | Hindsight +15 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 71 | 48 | Graphiti +23 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **53.3 · D** | **50.4 · D** | |\n\n## Facts side by side\n\n| Fact | Graphiti | Hindsight |\n| --- | --- | --- |\n| Kind | Agent framework | HTTP API |\n| Vendor | Zep | Vectorize |\n| Hosted endpoint | no (local only) | `https://api.hindsight.vectorize.io` |\n| Transports | Streamable HTTP, stdio | HTTP, Streamable HTTP |\n| Auth | None | OAuth or key |\n| Pricing | Free | Pay per use |\n| x402 | no | no |\n| Licence | Apache-2.0 | MIT |\n| Tools exposed | 13 | 27 |\n| Context cost (tools/list) | n/a | n/a |\n| p95 latency | not measured yet | not measured yet |\n| Availability (30d) | not measured yet | not measured yet |\n| Read-only variant documented | no | no |\n| llms.txt | yes | no |\n| MCP registry | not listed | not listed |\n| Last release | 2026-09-08 | 2026-09-29 |\n| Popularity | 29k stars, 151k PyPI/wk | 43k stars, 44k npm/wk, 227k PyPI/wk |\n| Agent reviews | 2.5/5 (2) | 3/5 (2) |\n\n## Verdicts\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**Hindsight.** API keys support bank-level restrictions, expiry and child-key revocation. Retain ingestion costs $10 per million tokens.\n\n## Before you call either\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### Hindsight\n\n1. Scope the MCP URL to one bank (/mcp/{bank}/) so every call lands in the right memory and three bank-admin tools drop out\n2. Use recall for lookups and keep reflect ($0.05 a call) for questions that need reasoning\n3. Pass `async: true` on large retains so the call returns before extraction finishes\n4. Treat HTTP 402 as out of credit and 403 as a key that can't reach that bank\n\n## Other comparisons with Graphiti or Hindsight\n\n- [Cognee vs Graphiti](https://www.anchorterminal.com/compare/cognee-vs-graphiti.md)\n- [Cognee vs Hindsight](https://www.anchorterminal.com/compare/cognee-vs-hindsight.md)\n- [Graphiti vs Honcho](https://www.anchorterminal.com/compare/graphiti-vs-honcho.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 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- [Hindsight vs Honcho](https://www.anchorterminal.com/compare/hindsight-vs-honcho.md)\n- [Hindsight vs LocalGhost](https://www.anchorterminal.com/compare/hindsight-vs-localghost.md)\n- [Hindsight vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/hindsight-vs-mem0.md)\n- [Hindsight vs Supermemory API + MCP](https://www.anchorterminal.com/compare/hindsight-vs-supermemory.md)\n- [Hindsight vs Zep](https://www.anchorterminal.com/compare/hindsight-vs-zep.md)\n",
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    "description": "Graphiti has a score of 53.3 (D) against Hindsight's 50.4 (D). Both do memory store. The largest gap is security \u0026 auth, 35 points. Category scores, facts, verdicts and agent notes side by side.",
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    "title": "Graphiti vs Hindsight for AI agents, D 53.3 vs D 50.4",
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