#2222nd of 27 in Memory
basic-memory
MCP server that stores AI memory as Markdown notes with a knowledge graph
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- Stars
- 4.5k
- License
- AGPL-3.0
- Last commit
- Nov 2026
- Last release
- Oct 2026
- Language
- Python
Missed the latest GitHub check; these facts may be older.
Overview
Basic Memory is a Python MCP server that lets Claude, Codex, Cursor, ChatGPT and other MCP clients read and write structured Markdown notes on your disk. Notes use observations and wikilink relations that form a traversable graph, indexed in local SQLite (or Postgres) with hybrid full-text and vector search. A hosted cloud edition is sold separately; the local version is free.
Who it is for: Users of Claude, Codex or Cursor who want persistent, file-based memory
Strengths
- Notes are plain Markdown files, editable in Obsidian or any editor, with two-way sync
- Hybrid full-text and vector search via FastEmbed, with optional cross-encoder reranking
- MCP tools carry read-only/destructive/idempotent hints; works with Claude, Codex, Cursor, VS Code
- Ships Claude Code, Hermes and OpenClaw plugins plus shared skills from the same repo
Weaknesses
- AGPL-3.0 license may be a problem for embedding in proprietary products
- Install needs uv and the --prerelease=allow flag due to a FastMCP 4 pre-release dependency
- Built-in cross-device sync and mobile access are in the paid cloud; local needs Git or Syncthing
- Reranking is off by default and adds latency plus a first-run model download
What it needs
- no GPU
- Docker + Compose
- Needs Python 3.12+, uv, SQLite (default) or Postgres, Milvus (optional), LiteLLM (optional)
- Models: Any MCP client (Claude, Codex, Cursor, VS Code, ChatGPT), FastEmbed embeddings, jinaai/jina-reranker-v1-tiny-en reranker
Also in Memory
See all 27| Rank | Project | Score |
|---|---|---|
| 1 | hindsightAgent memory server with retain, recall and reflect operations | 95 out of 100 |
| 2 | gbrainMemory store with sources and a knowledge graph for coding agents | 91 out of 100 |
| 3 | MemPalaceLocal verbatim memory store for AI agents with semantic search and MCP | 90 out of 100 |
| #4 | SupermemoryMemory and context engine for AI agents, with user profiles and hybrid search | 89 out of 100 |
| #5 | Mem0Long-term memory layer that stores and retrieves user facts for LLM agents | 88 out of 100 |