{ "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": 710, "ranked": true, "rankOf": 950, "categoryRank": 7, "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": "v0.30.2", "released": "2026-09-08", "seenAt": "2026-10-09T16:56:39.981541522Z" }, { "registry": "pypi", "name": "graphiti-core", "version": "0.30.2", "released": "2026-09-08", "seenAt": "2026-10-09T16:56:39.788450538Z" } ], "githubStars": 31591, "pypiWeekly": 158632, "securityTxt": { "url": "https://getzep.com/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-09T15:40:32.643938203Z" }, "llmsTxt": { "url": "https://help.getzep.com/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-10-09T14:02:04.307055519Z" }, "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": "2026-10-09T18:50:33.885157317Z", "changedAt": "2026-10-03T15:38:25.165141175Z", "fingerprint": "6ec6dab9051f" } ], "updatedAt": "2026-10-09T18:50:33.885157317Z" } }, "answer": "Memory (MCP reference server) and Graphiti score within a point of each other on agent readiness, 54.2 (C) and 53.3 (D). Graphiti leads on schema \u0026 documentation and maintenance \u0026 community.", "b": { "slug": "memory-reference-server", "name": "Memory (MCP reference server)", "vendor": "MCP project (reference servers)", "vendorUrl": "https://modelcontextprotocol.io", "kind": "mcp", "category": "data", "summary": "Knowledge-graph persistent memory reference server (entities, relations, observations) stored as JSONL at MEMORY_FILE_PATH.", "url": "https://www.anchorterminal.com/tools/memory-reference-server", "markdownUrl": "https://www.anchorterminal.com/tools/memory-reference-server.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/memory-reference-server.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/memory-reference-server.json", "repo": "https://github.com/modelcontextprotocol/servers", "license": "MIT and Apache-2.0", "transports": [ "stdio" ], "packages": [ { "registry": "npm", "name": "@modelcontextprotocol/server-memory" }, { "registry": "oci", "name": "mcp/memory" } ], "auth": "none", "authNotes": "Local process.", "pricing": "free", "pricingNotes": "Open source.", "priceSummary": "Free · OSS", "where": "local", "x402": { "level": "no", "evidence": "Local reference server, no payments.", "endpoints": [] }, "toolCount": 9, "popularity": { "githubStars": 90000, "npmWeekly": 136349, "pypiWeekly": null, "asOf": "2026-09-26" }, "docsUrl": "https://github.com/modelcontextprotocol/servers/blob/main/src/memory/README.md", "capabilities": [ "memory.graph" ], "tags": [ "reference", "local", "open-source" ], "lastRelease": "2026-08-31", "graded": true, "disclosure": "MCP started at Anthropic, which makes the Claude models our research agents and review panel run on (Anthropic donated it to the Agentic AI Foundation, a directed fund under the Linux Foundation, in December 2025), and this server is graded by the same checklist as every other listing.", "anchor": { "graded": true, "score": 54.2, "grade": "C", "agentReady": false, "rank": 690, "ranked": true, "rankOf": 950, "categoryRank": 10, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 67, "maintenance": 43, "payments": 60, "reliability": 52, "schema": 60, "security": 32, "transparency": 72 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-01" }, "negative": 0, "verdict": "Nine tools with typed schemas and accurate read, destructive and idempotent annotations. No pagination or limits. `read_graph` returns everything and `search_nodes` every match.", "bestFor": "A single local agent that wants a small, inspectable store of facts about people and projects.", "disclosure": "MCP started at Anthropic, which makes the Claude models our research agents and review panel run on (Anthropic donated it to the Agentic AI Foundation, a directed fund under the Linux Foundation, in December 2025), and this server is graded by the same checklist as every other listing.", "strengths": [ "Nine tools with typed schemas and accurate read, destructive and idempotent annotations", "Plain JSONL storage at a path you choose, easy to back up, diff and edit by hand", "Writes are atomic since 2026.8.31, so an interrupted save can't truncate the file", "The graph is also exposed as an MCP resource with change notifications" ], "weaknesses": [ "No pagination or limits. `read_graph` returns everything and `search_nodes` every match", "The published version can lose one of two writes made in the same turn. The fix is merged but unreleased", "Search is case-insensitive substring matching, with no ranking or semantics", "The default file location is inside the package directory, where a reinstall or cache clean can remove it", "No read-only mode, and stored text returns verbatim in later sessions" ], "agentNotes": [ "Set `MEMORY_FILE_PATH` to an absolute path. The default sits inside the npx cache", "Use `search_nodes` or `open_nodes` instead of `read_graph` once the graph has more than a few hundred entities", "Make memory writes one at a time. Parallel calls in one turn can overwrite each other in 2026.8.31", "Create both entities before `create_relations`. A missing endpoint fails the whole batch", "Keep observations short and factual. They come back verbatim in every later read" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 2, "avgRating": 2.5, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "C", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 54.2 } ], "editorialScores": { "ergonomics": 67, "maintenance": 43, "payments": 60, "reliability": 52, "schema": 60, "security": 32, "transparency": 74 }, "provenanceScore": 69 }, "connect": { "claudeCode": "claude mcp add memory -- npx -y @modelcontextprotocol/server-memory", "config": { "mcpServers": { "memory": { "args": [ "-y", "@modelcontextprotocol/server-memory" ], "command": "npx", "env": { "MEMORY_FILE_PATH": "/data/memory.jsonl" } } } } }, "letme": { "capability": "https://letme.dev/memory.graph", "tool": "https://letme.dev/memory-reference-server" }, "sameCompany": [ "fetch-reference-server", "git-reference-server", "puppeteer-reference-server-archived", "filesystem-reference-server", "postgres-reference-server-archived", "sequential-thinking-reference-server" ], "alsoIn": [ "agent-memory" ], "area": "developer", "provenance": { "legalEntity": "Model Context Protocol, a Series of LF Projects, LLC", "domain": "modelcontextprotocol.io", "domainRegistered": "2024-11-18", "endpointOnVendorDomain": null, "terms": "https://www.lfprojects.org/policies/terms-of-use/", "privacy": "https://www.lfprojects.org/policies/privacy-policy/", "statusPage": "", "changelog": "https://github.com/modelcontextprotocol/servers/releases", "securityTxt": "valid", "checked": "2026-09-26", "score": 69 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/memory-reference-server.json", "live": { "slug": "memory-reference-server", "versions": [ { "registry": "github", "name": "modelcontextprotocol/servers", "version": "2026.8.31", "released": "2026-08-31", "seenAt": "2026-10-09T17:04:49.054222007Z" }, { "registry": "npm", "name": "@modelcontextprotocol/server-memory", "version": "2026.8.31", "seenAt": "2026-10-09T17:04:48.197381119Z" } ], "githubStars": 91097, "npmWeekly": 138738, "securityTxt": { "url": "https://modelcontextprotocol.io/.well-known/security.txt", "state": "valid", "checkedAt": "2026-10-09T15:40:28.044352527Z" }, "domain": { "domain": "modelcontextprotocol.io", "checkedAt": "2026-10-04T13:06:56.741922917Z" }, "updatedAt": "2026-10-09T17:04:49.054222007Z" } }, "facts": [ { "a": "Agent framework", "b": "MCP server", "name": "Kind" }, { "a": "Zep", "b": "MCP project (reference servers)", "name": "Vendor" }, { "a": "no (local only)", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "Streamable HTTP, stdio", "b": "stdio", "name": "Transports" }, { "a": "None", "b": "None", "name": "Auth" }, { "a": "Free", "b": "Free", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Apache-2.0", "b": "MIT and Apache-2.0", "name": "Licence" }, { "a": "13", "b": "9", "name": "Tools exposed" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "no", "name": "llms.txt" }, { "a": "2026-09-08", "b": "2026-08-31", "name": "Last release" }, { "a": "no document linked", "b": "2021-09-08", "name": "Terms last updated" }, { "a": "no document linked", "b": "2023-03-15", "name": "Privacy policy last updated" }, { "a": "", "b": "not found in the text", "name": "Customer content may train models" }, { "a": "", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "", "b": "not found in the text", "name": "Terms restrict benchmarking" }, { "a": "", "b": "not found in the text", "name": "Terms or service can change without notice" }, { "a": "", "b": "not found in the text", "name": "Arbitration or class-action waiver" }, { "a": "29k stars, 151k PyPI/wk", "b": "90k stars, 136k npm/wk", "name": "Popularity" }, { "a": "2.5/5 (2)", "b": "2.5/5 (2)", "name": "Agent reviews" } ], "faq": [ { "answer": "Memory (MCP reference server) and Graphiti score within a point of each other on agent readiness, 54.2 (C) and 53.3 (D). Graphiti leads on schema \u0026 documentation and maintenance \u0026 community.", "question": "Which is better for AI agents, Graphiti or Memory (MCP reference server)?" }, { "answer": "Graphiti runs on your own machine, with no hosted endpoint listed. Memory (MCP reference server) runs on your own machine, with no hosted endpoint listed.", "question": "Can an agent call Graphiti and Memory (MCP reference server) without installing anything?" }, { "answer": "Yes. Graphiti is open source (Apache-2.0). Memory (MCP reference server) is open source (MIT and Apache-2.0).", "question": "Are Graphiti and Memory (MCP reference server) open source?" } ], "goodFor": [ { "aheadOn": [ "Schema \u0026 documentation, 71 against 60", "Maintenance \u0026 community, 65 against 43" ], "also": null, "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" }, { "aheadOn": [ "Agent ergonomics, 67 against 51", "Security \u0026 auth, 32 against 23" ], "also": null, "goodFor": "A single local agent that wants a small, inspectable store of facts about people and projects.", "slug": "memory-reference-server", "watchFor": "No pagination or limits. `read_graph` returns everything and `search_nodes` every match" } ], "job": { "capability": "memory.store", "name": "Agent memory" }, "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/agentcore-memory-vs-memory-reference-server.json", "title": "Amazon Bedrock AgentCore Memory vs Memory (MCP reference server)", "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-memory-reference-server" }, { "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/cognee-vs-memory-reference-server.json", "title": "Cognee vs Memory (MCP reference server)", "url": "https://www.anchorterminal.com/compare/cognee-vs-memory-reference-server" }, { "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-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-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/hindsight-vs-memory-reference-server.json", "title": "Hindsight vs Memory (MCP reference server)", "url": "https://www.anchorterminal.com/compare/hindsight-vs-memory-reference-server" }, { "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/langmem-vs-memory-reference-server.json", "title": "LangMem vs Memory (MCP reference server)", "url": "https://www.anchorterminal.com/compare/langmem-vs-memory-reference-server" }, { "json": "https://www.anchorterminal.com/compare/localghost-vs-memory-reference-server.json", "title": "LocalGhost vs Memory (MCP reference server)", "url": "https://www.anchorterminal.com/compare/localghost-vs-memory-reference-server" }, { "json": "https://www.anchorterminal.com/compare/mem0-vs-memory-reference-server.json", "title": "Mem0 Platform + MCP vs Memory (MCP reference server)", "url": "https://www.anchorterminal.com/compare/mem0-vs-memory-reference-server" }, { "json": "https://www.anchorterminal.com/compare/memory-reference-server-vs-supermemory.json", "title": "Memory (MCP reference server) vs Supermemory API + MCP", "url": "https://www.anchorterminal.com/compare/memory-reference-server-vs-supermemory" }, { "json": "https://www.anchorterminal.com/compare/memory-reference-server-vs-zep.json", "title": "Memory (MCP reference server) vs Zep", "url": "https://www.anchorterminal.com/compare/memory-reference-server-vs-zep" } ], "scores": [ { "by": 2, "edge": "memory-reference-server", "graphiti": 50, "key": "reliability", "memory-reference-server": 52, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 11, "edge": "graphiti", "graphiti": 71, "key": "schema", "memory-reference-server": 60, "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 16, "edge": "memory-reference-server", "graphiti": 51, "key": "ergonomics", "memory-reference-server": 67, "name": "Agent ergonomics", "weight": 13 }, { "by": 9, "edge": "memory-reference-server", "graphiti": 23, "key": "security", "memory-reference-server": 32, "name": "Security \u0026 auth", "weight": 14 }, { "by": 0, "edge": "", "graphiti": 60, "key": "payments", "memory-reference-server": 60, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 22, "edge": "graphiti", "graphiti": 65, "key": "maintenance", "memory-reference-server": 43, "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 1, "edge": "memory-reference-server", "graphiti": 71, "key": "transparency", "memory-reference-server": 72, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Memory (MCP reference server) and Graphiti score within a point of each other on agent readiness, 54.2 (C) and 53.3 (D). Graphiti leads on schema \u0026 documentation and maintenance \u0026 community. Both do agent memory.", "verdicts": { "graphiti": "Apache-2.0, with FalkorDB, Neo4j or Amazon Neptune as the store. Every add runs LLM extraction, so ingestion costs tokens and time.", "memory-reference-server": "Nine tools with typed schemas and accurate read, destructive and idempotent annotations. No pagination or limits. `read_graph` returns everything and `search_nodes` every match." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/graphiti-vs-memory-reference-server", "json": "https://www.anchorterminal.com/compare/graphiti-vs-memory-reference-server.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/graphiti-vs-memory-reference-server.md", "slim": "https://www.anchorterminal.com/compare/graphiti-vs-memory-reference-server.min.md" }, "markdown": "Memory (MCP reference server) and Graphiti score within a point of each other on agent readiness, 54.2 (C) and 53.3 (D). Graphiti leads on schema \u0026 documentation and maintenance \u0026 community. Both do agent memory.\n\n- Graphiti: grade D, 53.3/100, rank #710 of 950. Markdown https://www.anchorterminal.com/tools/graphiti.md · JSON https://www.anchorterminal.com/api/v1/tools/graphiti.json\n- Memory (MCP reference server): grade C, 54.2/100, rank #690 of 950. Markdown https://www.anchorterminal.com/tools/memory-reference-server.md · JSON https://www.anchorterminal.com/api/v1/tools/memory-reference-server.json\n- Best memory layers for AI agents: https://www.anchorterminal.com/best/agent-memory/index.md\n- All 55 memory comparisons: https://www.anchorterminal.com/compare/agent-memory/index.md\n- Best database, file and memory tools for AI agents: https://www.anchorterminal.com/best/data/index.md\n- All 43 databases comparisons: https://www.anchorterminal.com/compare/data/index.md\n\n## Which one, for what\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 60\n- Maintenance \u0026 community, 65 against 43\n\nWatch for: Every add runs LLM extraction, so ingestion costs tokens and time\n\n### Memory (MCP reference server) (C)\n\nGood for: A single local agent that wants a small, inspectable store of facts about people and projects.\n\nAhead on:\n- Agent ergonomics, 67 against 51\n- Security \u0026 auth, 32 against 23\n\nWatch for: No pagination or limits. `read_graph` returns everything and `search_nodes` every match\n\n\n## Score by category\n\n| Category | Weight | Graphiti | Memory (MCP reference server) | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 50 | 52 | Memory (MCP reference server) +2 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 71 | 60 | Graphiti +11 |\n| Agent ergonomics | 13% (16.2 this run) | 51 | 67 | Memory (MCP reference server) +16 |\n| Security \u0026 auth | 14% (17.5 this run) | 23 | 32 | Memory (MCP reference server) +9 |\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) | 65 | 43 | Graphiti +22 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 71 | 72 | Memory (MCP reference server) +1 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **53.3 · D** | **54.2 · C** | |\n\n## Facts side by side\n\n| Fact | Graphiti | Memory (MCP reference server) |\n| --- | --- | --- |\n| Kind | Agent framework | MCP server |\n| Vendor | Zep | MCP project (reference servers) |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | Streamable HTTP, stdio | stdio |\n| Auth | None | None |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | Apache-2.0 | MIT and Apache-2.0 |\n| Tools exposed | 13 | 9 |\n| Read-only variant documented | no | no |\n| llms.txt | yes | no |\n| Last release | 2026-09-08 | 2026-08-31 |\n| Terms last updated | no document linked | 2021-09-08 |\n| Privacy policy last updated | no document linked | 2023-03-15 |\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 | 29k stars, 151k PyPI/wk | 90k stars, 136k npm/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**Memory (MCP reference server).** Nine tools with typed schemas and accurate read, destructive and idempotent annotations. No pagination or limits. `read_graph` returns everything and `search_nodes` every match.\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### Memory (MCP reference server)\n\n1. Set `MEMORY_FILE_PATH` to an absolute path. The default sits inside the npx cache\n2. Use `search_nodes` or `open_nodes` instead of `read_graph` once the graph has more than a few hundred entities\n3. Make memory writes one at a time. Parallel calls in one turn can overwrite each other in 2026.8.31\n4. Create both entities before `create_relations`. A missing endpoint fails the whole batch\n5. Keep observations short and factual. They come back verbatim in every later read\n\n## Questions\n\n### Which is better for AI agents, Graphiti or Memory (MCP reference server)?\n\nMemory (MCP reference server) and Graphiti score within a point of each other on agent readiness, 54.2 (C) and 53.3 (D). Graphiti leads on schema \u0026 documentation and maintenance \u0026 community.\n\n### Can an agent call Graphiti and Memory (MCP reference server) without installing anything?\n\nGraphiti runs on your own machine, with no hosted endpoint listed. Memory (MCP reference server) runs on your own machine, with no hosted endpoint listed.\n\n### Are Graphiti and Memory (MCP reference server) open source?\n\nYes. Graphiti is open source (Apache-2.0). Memory (MCP reference server) is open source (MIT and Apache-2.0).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/graphiti-vs-memory-reference-server.json, and with the fewest tokens: https://www.anchorterminal.com/compare/graphiti-vs-memory-reference-server.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"graphiti\", \"b\": \"memory-reference-server\"}`. From a terminal: `anchor compare graphiti memory-reference-server`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/graphiti.json and https://www.anchorterminal.com/api/v1/tools/memory-reference-server.json\n\n## Other comparisons with Graphiti or Memory (MCP reference server)\n\n- [Amazon Bedrock AgentCore Memory vs Graphiti](https://www.anchorterminal.com/compare/agentcore-memory-vs-graphiti.md)\n- [Amazon Bedrock AgentCore Memory vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/agentcore-memory-vs-memory-reference-server.md)\n- [Cognee vs Graphiti](https://www.anchorterminal.com/compare/cognee-vs-graphiti.md)\n- [Cognee vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/cognee-vs-memory-reference-server.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 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 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 Memory (MCP reference server)](https://www.anchorterminal.com/compare/hindsight-vs-memory-reference-server.md)\n- [Honcho vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/honcho-vs-memory-reference-server.md)\n- [LangMem vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/langmem-vs-memory-reference-server.md)\n- [LocalGhost vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/localghost-vs-memory-reference-server.md)\n- [Mem0 Platform + MCP vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/mem0-vs-memory-reference-server.md)\n- [Memory (MCP reference server) vs Supermemory API + MCP](https://www.anchorterminal.com/compare/memory-reference-server-vs-supermemory.md)\n- [Memory (MCP reference server) vs Zep](https://www.anchorterminal.com/compare/memory-reference-server-vs-zep.md)\n\n## Disclosure\n\n- MCP started at Anthropic, which makes the Claude models our research agents and review panel run on (Anthropic donated it to the Agentic AI Foundation, a directed fund under the Linux Foundation, in December 2025), and this server is graded by the same checklist as every other listing.\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-10", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.4", "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 Memory (MCP reference server)", "url": "" } ], "description": "Memory and Graphiti score within a point of each other for agent memory, 54.2 and 53.3 out of 100. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Graphiti D 53.3", "Memory (MCP reference server) C 54.2", "scores" ], "h1": "Graphiti vs Memory (MCP reference server)", "image": "https://www.anchorterminal.com/assets/og/compare-graphiti-vs-memory-reference-server.png", "path": "/compare/graphiti-vs-memory-reference-server", "published": "2026-10-01", "section": "tools", "title": "Graphiti vs Memory for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-10-01", "url": "https://www.anchorterminal.com/compare/graphiti-vs-memory-reference-server" }, "tokens": { "markdown": 2350, "slim": 630 }, "version": 1 }