{"data":{"slug":"verygoodplugins-automem","name":"automem","tagline":"Graph-vector memory service for durable, relational AI assistant memory","github_url":"https://github.com/verygoodplugins/automem","owner":"verygoodplugins","repo":"automem","owner_avatar_url":"https://avatars.githubusercontent.com/u/193913467?v=4","primary_language":"Python","stars":813,"forks":105,"topics":["ai","ai-memory","anthropic","automem","falkordb","graph-database","llm","memory","qdrant","rag","vector-database"],"archived":false,"github_pushed_at":"2026-09-10T13:20:46+00:00","maintenance_label":"Active","stars_delta_30d":20,"url":"https://www.graphcanon.com/tools/verygoodplugins-automem","markdown_url":"https://www.graphcanon.com/tools/verygoodplugins-automem.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/verygoodplugins-automem","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=verygoodplugins-automem","description":"Long-term memory for AI assistants. Graph + vector store that recalls decisions, relationships, and context across sessions.","homepage_url":"https://automem.ai/","license":"MIT","open_issues":12,"watchers":9,"ai_summary":"AutoMem is a tool in Python that enables AI assistants to have persistent and relationship-aware memory by utilizing graph and vector database technologies.","readme_excerpt":"### Docker Compose (local)\n\n```bash\ngit clone https://github.com/verygoodplugins/automem.git\ncd automem\nmake dev\n```\n\n| Service | URL | Purpose |\n|---|---|---|\n| AutoMem API | `http://localhost:8001` | Memory REST API |\n| FalkorDB | `localhost:6379` | Graph database |\n| Qdrant | `localhost:6333` | Vector database |\n| FalkorDB Browser | `http://localhost:3000` | Local graph inspection UI |\n\n→ Full setup: [INSTALLATION.md](INSTALLATION.md#docker-compose-local)\n\n---\n\n## Docs, community, and license\n\n**Setup**\n- [Installation guide](INSTALLATION.md) — Railway, Docker, development\n- [Qdrant setup](docs/QDRANT_SETUP.md) — vector database configuration\n- [Environment variables](docs/ENVIRONMENT_VARIABLES.md) — full reference\n\n**API and integration**\n- [API reference](docs/API.md) — endpoints, scoring, enrichment\n- [Remote MCP](docs/MCP_SSE.md) — ChatGPT, Claude.ai, ElevenLabs\n- [Migrations](docs/MIGRATIONS.md) — embedding dimensions, 0.16.0 data migrations, MCP SQLite import\n\n**Research and comparison**\n- [Research foundation](docs/RESEARCH.md) — papers and how AutoMem implements them\n- [Comparison](docs/COMPARISON.md) — vs. RAG, vector DBs, building your own\n- [Benchmark history](benchmarks/EXPERIMENT_LOG.md) — internal LoCoMo / LongMemEval harness runs + the neutral AMB (BEAM + Core-3) summary\n- [AMB head-to-head + reproducibility](https://automem.ai/benchmarks) — neutral Agent Memory Benchmark results and the `AUTOMEM_REPRODUCE.md` \"run it yourself\" recipe\n\n**Operations**\n- [Scripts](scripts/README.md) — maintenance, migration, recovery, and eval tooling, by lifecycle\n- [Health monitoring & backups](docs/MONITORING_AND_BACKUPS.md)\n- [Testing guide](docs/TESTING.md) — unit, integration, benchmarks\n\n**Community**\n- [automem.ai](https://automem.ai) — official site\n- [Discord](https://automem.ai/discord) — community chat\n- [X / @automem_ai](https://x.com/automem_ai) — updates\n- [YouTube / @AutoJackBot](https://www.youtube.com/@AutoJackBot) — tutorials\n- [GitHub issues](https://github.com/verygoodplugins/automem/issues) — bugs and feature requests\n\n**Sibling repos**\n- [`mcp-automem`](https://github.com/verygoodplugins/mcp-automem) — universal MCP bridge / install funnel\n- [`automem-evals`](https://github.com/verygoodplugins/automem-evals) — exploratory recall-quality lab\n- [`automem-graph-viewer`](https://github.com/verygoodplugins/automem-graph-viewer) — standalone graph visualization\n\nMIT licensed. Deploy anywhere. No vendor lock-in.","github_created_at":"2025-09-16T07:04:22+00:00","created_at":"2026-07-11T11:27:20.195656+00:00","updated_at":"2026-09-20T06:06:59.78518+00:00","categories":[{"slug":"ai-agents","name":"AI Agents","url":"https://www.graphcanon.com/categories/ai-agents","markdown_url":"https://www.graphcanon.com/categories/ai-agents.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/ai-agents"},{"slug":"vector-databases","name":"Vector Databases","url":"https://www.graphcanon.com/categories/vector-databases","markdown_url":"https://www.graphcanon.com/categories/vector-databases.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/vector-databases"}],"tags":[{"slug":"ai-memory","name":"ai-memory"},{"slug":"anthropic","name":"anthropic"},{"slug":"falkordb","name":"falkordb"},{"slug":"graph-database","name":"graph-database"},{"slug":"llm","name":"llm"},{"slug":"qdrant","name":"qdrant"},{"slug":"vector-database","name":"vector-database"}],"trust":{"provenance":{"is_fork":false,"github_id":1057758059,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-09-20T06:06:57.025Z","maintenance":{"label":"Active","score":82,"methodology":"github_public_v1","releases_90d":3,"days_since_push":9,"last_release_at":"2026-08-28T18:01:26Z","stars_delta_30d":20,"open_issues_delta_30d":1},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:27:21.349Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-09-20T06:06:58.079Z"},"deploy":{"source":"dockerfile:Dockerfile","self_host":true,"observed_at":"2026-09-20T06:06:58.079Z","managed_saas":false},"languages":{"value":["python"],"source":"github.language+pyproject.toml","observed_at":"2026-09-20T06:06:58.079Z"},"has_docker":{"value":true,"source":"dockerfile:Dockerfile","observed_at":"2026-09-20T06:06:58.079Z"},"license_spdx":{"value":"MIT","source":"github.license","observed_at":"2026-09-20T06:06:58.079Z"}},"decision_facts":{"hosting":null,"pricing":{"model":"freemium","summary":"Free for open-source use, with no explicit commercial licensing information provided."},"requirements":{"min_ram_gb":null,"requires_docker":false},"constraints":{"min_ram_gb":null,"pricing_model":"freemium","requires_docker":false},"when_to_use":["Use AutoMem when you need an AI assistant capable of maintaining rich, relational memories over time.","Ideal for applications where AI needs to recall not just information but also the relationships between pieces of data."],"when_not_to_use":["Avoid using AutoMem if your application does not benefit from persistent memory or relational context, as it might add unnecessary overhead.","If you require a simpler key-value storage system for less complex or non-relational data, AutoMem's graph and vector capabilities may be overkill."],"source":"enrich:decision_facts","observed_at":"2026-07-12T16:16:40.406Z"},"constraint_facets":{"min_ram_gb":null,"pricing_model":"freemium","requires_docker":false},"decision_summary":[{"label":"Pricing","value":"freemium - Free for open-source use, with no explicit commercial licensing information provided."},{"label":"Adopt for","value":"AutoMem leverages both graph and vector database technologies to provide AI assistants with durable relational memory."},{"label":"License detail","value":"AutoMem is licensed under the MIT License, which means it is free to use, modify, and distribute as long as license terms are met."}]}}