🎯 recall

One query across an agent's whole memory.

An agent's knowledge ends up scattered: some in its second brain (cortex), some in the team's shared memory (agent-hq), some in what it's read (scout), some in its code (lens). Searching each by hand is friction — so agents skip it and re-derive what they already knew. recall fixes that: one query, every store, one ranked briefing — token-budgeted, each hit tagged by source. Run it at the start of a task to load exactly the relevant context.

Part of tools-for-agents. Zero dependencies — node:sqlite over the sibling tools' existing FTS5 indexes, read-only. It doesn't own any data; it federates theirs. Any store that isn't present is simply skipped.

Why

Related MCP server: Veridge MCP Server

The stores

Each store is optional and auto-discovered — the team store is included whenever agent-hq is reachable, and skipped (fast) when it isn't.

CLI

recall "auth token refresh design"            # everything you know about it
recall "kafka retries" -k 12 --tokens 3000    # more hits, bigger budget
recall "graph traversal" --only brain,code    # restrict to some stores
recall status                                 # which stores are available + counts

MCP server (for agents)

{
  "mcpServers": {
    "recall": { "command": "node", "args": ["/abs/path/to/recall/mcp/mcp-server.js"],
      "env": { "CORTEX_VAULT": "/abs/path/to/vault", "SCOUT_DB": "/abs/path/to/.scout/cache.db",
               "LENS_DB": "/abs/path/to/.lens/index.db", "HQ_URL": "http://localhost:7700" } }
  }
}

Tools

How it works

• Runs the query as an FTS5 MATCH against each store's index and normalises every hit to { source, title, ref, meta, excerpt, score }.

• bm25 scores aren't comparable across separate databases, so results are interleaved round-robin across sources (best-of-each, then next-best-of-each…) and filled to a token budget — a balanced briefing rather than one store drowning out the rest.

• SQLite stores are opened read-only; recall never writes. Delete or rebuild any underlying index freely.

• The team store is queried over agent-hq's HTTP memory API (per-term, in parallel, with a short timeout) and degrades silently when the platform isn't running.

• It depends only on the sibling tools' stable interfaces — their table schemas (notes_fts, pages_fts, chunks) and agent-hq's /api/memory — not their code, so each tool stays independent.