recall-mcp

Persistent, searchable memory for AI agents — over the Model Context Protocol.

Give any MCP-capable agent (Claude Code, Claude Desktop, Cursor, Windsurf, ...) a long-term memory it can write to and search across sessions. Facts, preferences, decisions, and lessons survive restarts and are retrieved by relevance-ranked full-text search.

• 🧠 Six tools: save, search, recent, get, forget, stats
• 🔎 Real search: SQLite FTS5 with BM25 ranking, porter stemming, and an importance boost — not a LIKE '%...%' scan
• 📦 Zero native dependencies: uses Node's built-in node:sqlite (Node ≥ 23.4). No compilers, no prebuilt binaries, nothing to break on install
• 🗃️ Single-file storage: one SQLite database at ~/.recall-mcp/memories.db (WAL mode), easy to back up or inspect

Quick start

git clone https://github.com/jadeleke/recall-mcp.git
cd recall-mcp
npm install
npm run build

Claude Code

claude mcp add recall -- node /path/to/recall-mcp/dist/index.js

Claude Desktop / other MCP clients

Add to your MCP config (e.g. claude_desktop_config.json):

{
  "mcpServers": {
    "recall": {
      "command": "node",
      "args": ["/path/to/recall-mcp/dist/index.js"]
    }
  }
}

Tools

Tool	What it does
memory_save	Persist a fact with optional tags and importance (1–5)
memory_search	Full-text search, BM25-ranked with importance boost. FTS5 syntax (phrases, AND/OR/NEAR) supported; plain queries work too
memory_recent	Most recently saved/updated memories, newest first
memory_get	Fetch one memory by id
memory_forget	Permanently delete a memory by id
memory_stats	Totals, tag histogram, date range, db location and size

Example

An agent mid-conversation:

memory_save({
  content: "User deploys to Fly.io from CI only — never deploy from a laptop",
  tags: ["ops", "user-preference"],
  importance: 5
})

Weeks later, in a fresh session:

memory_search({ query: "how does the user deploy" })

returns the fact, ranked first thanks to porter stemming (deploy matches deploys) and the importance boost.

Configuration

Env var	Default	Purpose
RECALL_DB	~/.recall-mcp/memories.db	Database file path. Set per-project paths to keep separate memory stores; :memory: for ephemeral

Development

npm test        # node:test suite — runs TypeScript directly via Node's type stripping
npm run build   # emits dist/

The codebase is small on purpose: src/store.ts is the storage layer (schema, FTS5 triggers, search), src/index.ts wires it to MCP over stdio.

Why not just a system prompt?

System prompts are per-session and hand-curated. recall-mcp lets the agent decide what's worth keeping, accumulates knowledge across every session and every MCP client that shares the database, and retrieves only what's relevant to the current task instead of stuffing everything into context.

License

MIT