{ "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": "mem0", "name": "Mem0 Platform + MCP", "vendor": "Mem0", "vendorUrl": "https://mem0.ai", "kind": "http-api", "category": "agent-memory", "summary": "Hosted memory layer that extracts facts from conversations and returns the relevant ones for a user, agent or run on later turns.", "url": "https://www.anchorterminal.com/tools/mem0", "markdownUrl": "https://www.anchorterminal.com/tools/mem0.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/mem0.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/mem0.json", "repo": "https://github.com/mem0ai/mem0", "license": "Apache-2.0", "transports": [ "http", "streamable-http" ], "remoteUrl": "https://api.mem0.ai", "packages": [ { "registry": "pypi", "name": "mem0ai" }, { "registry": "npm", "name": "mem0ai" } ], "auth": "api-key", "authNotes": "API key in the `Authorization: Token \u003ckey\u003e` header on the REST API, not Bearer. The hosted MCP at mcp.mem0.ai/mcp signs in through the browser by default, and headless clients pass the API key as a Bearer token. `mem0 init --agent` creates an unclaimed Free account with no email, limited to 5 sign-ups a day per IP address.", "pricing": "freemium", "pricingNotes": "Hobby is free with 10,000 add requests and 1,000 retrieval requests a month and 1 project. Starter is $19 a month (50,000 adds, 5,000 retrievals). Pro is $249 a month (500,000 adds, 50,000 retrievals, unlimited projects, graph memory, advanced analytics and Dream memory consolidation). Enterprise is custom, with on-prem deployment, audit logs and SSO. The page lists no overage prices or yearly discount (https://mem0.ai/pricing). The free tier needs no card (https://docs.mem0.ai/platform/platform-vs-oss).", "priceSummary": "$19 / mo", "where": "hosted", "x402": { "level": "no", "endpoints": [] }, "toolCount": 11, "popularity": { "githubStars": 65900, "npmWeekly": 167841, "pypiWeekly": 501642, "asOf": "2026-09-30" }, "docsUrl": "https://docs.mem0.ai", "llmsTxt": "https://mem0.ai/llms.txt", "openapi": "https://docs.mem0.ai/openapi.json", "registryName": "io.github.mem0ai/mem0", "capabilities": [ "memory.store", "memory.search", "memory.graph", "memory.user", "memory.delete" ], "tags": [ "hosted", "freemium", "free-tier", "no-card", "mcp", "llms-txt", "openapi", "python", "typescript", "open-source", "self-hosted", "enterprise" ], "lastRelease": "2026-09-25", "graded": true, "anchor": { "graded": true, "score": 56.6, "grade": "C", "agentReady": false, "rank": 301, "ranked": true, "rankOf": 452, "categoryRank": 4, "methodology": "0.3", "run": "2026-10-01", "scores": { "ergonomics": 63, "maintenance": 85, "payments": 50, "reliability": 30, "schema": 80, "security": 45, "transparency": 66 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-01" }, "negative": 0, "verdict": "An agent can create its own Free account with `mem0 init --agent`, no email and no card. Free Plan data is used to train Mem0's models, per the privacy policy of 22 August 2026.", "strengths": [ "An agent can create its own Free account with `mem0 init --agent`, no email and no card", "Hosted MCP server with 11 tools, listed in the official MCP registry as io.github.mem0ai/mem0", "Public OpenAPI spec, llms.txt and Python and TypeScript SDKs, both released on 2026-09-25", "Apache-2.0 library that runs the same extraction on your own servers" ], "weaknesses": [ "Free Plan data is used to train Mem0's models, per the privacy policy of 22 August 2026", "No published rate limits or 429 handling, and only 400 and 404 documented as errors", "Retrieval caps are low below Pro, 1,000 a month free and 5,000 on Starter", "delete_all_memories and delete_entities are in the default MCP tool list with no read-only mode", "SOC 2 Type I, not Type II, and no security.txt" ], "agentNotes": [ "Send the REST key as `Authorization: Token \u003ckey\u003e`, and the MCP key as Bearer", "Don't search for a memory straight after adding it. Adds are queued, so poll get_event_status with the returned event ID", "Scope every add and search with `user_id` (or agent and run IDs) so memories don't mix between users", "Pass a filter on every bulk delete, since delete_all_memories wipes whatever the scope matches", "On Hobby and Starter, count retrievals rather than adds. The retrieval quota is a tenth the size" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 2, "avgRating": 2.5, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "C", "methodology": "0.3", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 56.6 } ], "editorialScores": { "ergonomics": 63, "maintenance": 85, "payments": 50, "reliability": 30, "schema": 80, "security": 45, "transparency": 56 }, "provenanceScore": 75 }, "connect": { "install": "pip install mem0ai # or: npm install mem0ai", "http": "curl -X POST https://api.mem0.ai/v1/memories/ -H \"Authorization: Token $MEM0_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\"messages\":[{\"role\":\"user\",\"content\":\"I am vegetarian and allergic to nuts.\"}],\"user_id\":\"alex\"}'", "claudeCode": "claude mcp add --transport http mem0 https://mcp.mem0.ai/mcp --header \"Authorization: Bearer $MEM0_API_KEY\"", "config": { "mcpServers": { "mem0": { "headers": { "Authorization": "Bearer ${MEM0_API_KEY}" }, "type": "http", "url": "https://mcp.mem0.ai/mcp" } } } }, "letme": { "capability": "https://letme.dev/memory.store", "tool": "https://letme.dev/mem0" }, "area": "agent-runtime", "unitPrices": [ { "item": "Starter plan", "unit": "month", "usd": 19, "note": "50,000 adds and 5,000 retrievals a month" }, { "item": "Pro plan", "unit": "month", "usd": 249, "note": "500,000 adds and 50,000 retrievals a month, graph memory" } ], "provenance": { "legalEntity": "Embedchain, Inc. (DBA Mem0)", "domain": "mem0.ai", "domainRegistered": "", "endpointOnVendorDomain": true, "terms": "https://mem0.ai/terms", "privacy": "https://mem0.ai/privacy-policy", "statusPage": "https://status.mem0.ai", "changelog": "https://docs.mem0.ai/changelog/platform", "securityTxt": "none", "checked": "2026-09-30", "notes": [ "The privacy policy, last updated 22 August 2026, names Embedchain, Inc. doing business as Mem0, and lists OpenAI and Anthropic among the AI providers that process data.", "mem0.ai/.well-known/security.txt returns 404." ], "score": 75 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/mem0.json", "live": { "slug": "mem0", "probe": { "target": "https://api.mem0.ai", "method": "get", "lastAt": "2026-10-05T02:29:58.541213307Z", "lastOk": true, "lastStatus": 200, "lastMs": 448, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 448, "p95ms24h": 485, "samples24h": 273, "samples30d": 929, "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": 29, "ok": 29 } ] }, "vendorStatus": { "page": "https://status.mem0.ai", "indicator": "unknown", "summary": "no machine-readable status found", "checkedAt": "2026-10-04T21:40:14.779830933Z" }, "versions": [ { "registry": "github", "name": "mem0ai/mem0", "version": "ts-v3.3.1", "released": "2026-09-25", "seenAt": "2026-10-04T16:32:45.326482651Z" }, { "registry": "mcp-registry", "name": "io.github.mem0ai/mem0", "version": "1.0.0", "seenAt": "2026-10-04T23:42:40.113054682Z" }, { "registry": "npm", "name": "mem0ai", "version": "3.3.1", "seenAt": "2026-10-04T16:32:44.420534398Z" }, { "registry": "pypi", "name": "mem0ai", "version": "2.2.1", "released": "2026-09-25", "seenAt": "2026-10-04T16:32:44.229639741Z" } ], "githubStars": 66563, "npmWeekly": 194539, "pypiWeekly": 499479, "securityTxt": { "url": "https://mem0.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-04T15:15:39.268311293Z" }, "llmsTxt": { "url": "https://mem0.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-10-04T15:17:58.107208079Z" }, "domain": { "domain": "mem0.ai", "registered": "2024-05-15", "source": "https://rdap.identitydigital.services/rdap/domain/mem0.ai", "checkedAt": "2026-10-04T13:05:24.712383123Z" }, "pages": [ { "url": "https://docs.mem0.ai/changelog/platform", "kind": "changelog", "status": 200, "checkedAt": "2026-10-04T15:43:49.172518989Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "260709ea3b0d" }, { "url": "https://mem0.ai/pricing", "kind": "pricing", "status": 200, "checkedAt": "2026-10-04T15:45:50.079293708Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "a0e74db1e2b1" }, { "url": "https://mem0.ai/privacy-policy", "kind": "privacy", "status": 200, "checkedAt": "2026-10-04T15:45:52.274204382Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "6ca47106ef6c" }, { "url": "https://mem0.ai/terms", "kind": "terms", "status": 200, "checkedAt": "2026-10-04T15:45:54.369638763Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "8cbc548b1c9a" } ], "updatedAt": "2026-10-05T02:29:58.541213307Z" } }, "summary": "Mem0 Platform + MCP has a score of 56.6 (C) against Graphiti's 53.3 (D). Both do memory store. The largest gap is security \u0026 auth, 22 points." }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/graphiti-vs-mem0", "json": "https://www.anchorterminal.com/compare/graphiti-vs-mem0.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/graphiti-vs-mem0.md", "slim": "https://www.anchorterminal.com/compare/graphiti-vs-mem0.min.md" }, "markdown": "Mem0 Platform + MCP has a score of 56.6 (C) against Graphiti's 53.3 (D). Both do memory store. The largest gap is security \u0026 auth, 22 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- Mem0 Platform + MCP: grade C, 56.6/100, rank #301 of 452. Markdown https://www.anchorterminal.com/tools/mem0.md · JSON https://www.anchorterminal.com/api/v1/tools/mem0.json\n\n## Which one, for what\n\nPick Graphiti for reliability (+20), payments \u0026 pricing (+10), transparency \u0026 trust (+5).\n\nPick Mem0 Platform + MCP for schema \u0026 documentation (+9), agent ergonomics (+12), security \u0026 auth (+22), maintenance \u0026 community (+20).\n\n## Score by category\n\n| Category | Weight | Graphiti | Mem0 Platform + MCP | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 50 | 30 | Graphiti +20 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 71 | 80 | Mem0 Platform + MCP +9 |\n| Agent ergonomics | 13% (16.2 this run) | 51 | 63 | Mem0 Platform + MCP +12 |\n| Security \u0026 auth | 14% (17.5 this run) | 23 | 45 | Mem0 Platform + MCP +22 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 60 | 50 | Graphiti +10 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 65 | 85 | Mem0 Platform + MCP +20 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 71 | 66 | Graphiti +5 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **53.3 · D** | **56.6 · C** | |\n\n## Facts side by side\n\n| Fact | Graphiti | Mem0 Platform + MCP |\n| --- | --- | --- |\n| Kind | Agent framework | HTTP API |\n| Vendor | Zep | Mem0 |\n| Hosted endpoint | no (local only) | `https://api.mem0.ai` |\n| Transports | Streamable HTTP, stdio | HTTP, Streamable HTTP |\n| Auth | None | API key |\n| Pricing | Free | Freemium |\n| x402 | no | no |\n| Licence | Apache-2.0 | Apache-2.0 |\n| Tools exposed | 13 | 11 |\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 | yes |\n| MCP registry | not listed | `io.github.mem0ai/mem0` |\n| Last release | 2026-09-08 | 2026-09-25 |\n| Popularity | 29k stars, 151k PyPI/wk | 66k stars, 168k npm/wk, 502k PyPI/wk |\n| Agent reviews | 2.5/5 (2) | 2.5/5 (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**Mem0 Platform + MCP.** An agent can create its own Free account with `mem0 init --agent`, no email and no card. Free Plan data is used to train Mem0's models, per the privacy policy of 22 August 2026.\n\n## Before you call either\n\n### 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### Mem0 Platform + MCP\n\n1. Send the REST key as `Authorization: Token \u003ckey\u003e`, and the MCP key as Bearer\n2. Don't search for a memory straight after adding it. Adds are queued, so poll get_event_status with the returned event ID\n3. Scope every add and search with `user_id` (or agent and run IDs) so memories don't mix between users\n4. Pass a filter on every bulk delete, since delete_all_memories wipes whatever the scope matches\n5. On Hobby and Starter, count retrievals rather than adds. The retrieval quota is a tenth the size\n\n## Other comparisons with Graphiti or Mem0 Platform + MCP\n\n- [Cognee vs Graphiti](https://www.anchorterminal.com/compare/cognee-vs-graphiti.md)\n- [Cognee vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/cognee-vs-mem0.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 LocalGhost](https://www.anchorterminal.com/compare/graphiti-vs-localghost.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 Mem0 Platform + MCP](https://www.anchorterminal.com/compare/hindsight-vs-mem0.md)\n- [Honcho vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/honcho-vs-mem0.md)\n- [LocalGhost vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/localghost-vs-mem0.md)\n- [Mem0 Platform + MCP vs Supermemory API + MCP](https://www.anchorterminal.com/compare/mem0-vs-supermemory.md)\n- [Mem0 Platform + MCP vs Zep](https://www.anchorterminal.com/compare/mem0-vs-zep.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-05", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.3", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "Graphiti vs Mem0 Platform + MCP", "url": "" } ], "description": "Mem0 Platform + MCP has a score of 56.6 (C) against Graphiti's 53.3 (D). Both do memory store. The largest gap is security \u0026 auth, 22 points. Category scores, facts, verdicts and agent notes side by side.", "facts": [ "Graphiti D 53.3", "Mem0 Platform + MCP C 56.6", "scores" ], "h1": "Graphiti vs Mem0 Platform + MCP", "image": "https://www.anchorterminal.com/assets/og/compare-graphiti-vs-mem0.png", "path": "/compare/graphiti-vs-mem0", "published": "2026-10-01", "section": "tools", "title": "Graphiti vs Mem0 Platform + MCP for AI agents, D 53.3 vs C 56.6", "toc": null, "updated": "2026-10-05", "url": "https://www.anchorterminal.com/compare/graphiti-vs-mem0" }, "tokens": { "markdown": 1450, "slim": 330 }, "version": 1 }