suasor
A local-first AI secretary that gathers your work context into private memory and enables AI agents to search and summarize it over MCP.
README
Suasor
Gathers, remembers, advises - you decide.
Suasor is a local-first AI secretary. It gathers your scattered work context - chat, email, calendar, documents, code, the web - into private memory on your own machine, so you and your AI agents can search and summarize it over MCP. It advises you, and proposes replies, tasks, and decisions. Nothing is sent or saved without your approval.
What it does
- Gathers — pulls your scattered work context from across your tools into one local, private store. Read-only: it never writes back to your sources.
- Remembers — keeps it as searchable, queryable memory on your own machine.
- Advises — surfaces, summarizes, and proposes replies, tasks, and decisions over MCP. You and your AI agents query it; you approve everything. Nothing is sent or saved without your say.
Status
Early development. Suasor is being built spec-first.
Install
Distributed via four channels (released manually — see docs/guide/install.md):
- npm —
bunx @ozzylabs/suasor mcp serve(orbun add -g @ozzylabs/suasor). Canonical; OIDC-published with provenance. - Standalone binary — download per OS/arch from Releases. Core + a few native bits; the heavier connector SDKs are external (use npm/Docker for the full connector set).
- Docker (batteries-included + Ollama) —
docker run ghcr.io/ozzy-labs/suasor. Local embedding with no external egress. - MCP registry — discoverable via
server.json.
Until the first release is published, run from source with the Quickstart below.
Quickstart (provisional)
Early development, but every CLI command below is implemented (ingest, retrieval, MCP server, and skills all work). The only not-yet-shipped pieces are the
brief/graph.relatedMCP tools — see docs/design/mcp-surface.md. Requires Bun 1.1+.
bun install # install dependencies
bun run src/index.ts --version
# First-run setup: writes ~/.config/suasor/config.toml and the local SQLite store.
bun run src/index.ts init
# Ingest read-only from a connector (github / slack / ms-graph / google / box / web).
bun run src/index.ts github sync
# Full-text search over ingested sources (FTS5; --json / --limit available).
bun run src/index.ts search "<query>"
# Install the bundled assistant skills into your agent host(s).
bun run src/index.ts skills install # .claude/skills/ + .agents/skills/
bun run src/index.ts skills list # installed / missing / modified
# Maintenance.
bun run src/index.ts db migrate # apply the projection schema (idempotent)
bun run src/index.ts projections rebuild # replay the event log into projections
Config lives in ~/.config/suasor/ (override with SUASOR_CONFIG_DIR). <connector> sync ingests read-only from github / slack / ms-graph / google / box / web — see docs/guide/connectors.md for per-connector setup. See docs/design/cli.md for the full command/flag reference and docs/skills/README.md for the assistant skills.
Connect an agent host (MCP)
Suasor exposes its memory to AI agents over the Model Context Protocol (stdio transport). The server is the agent boundary. Read tools — search, recall.search, source.list / source.get, and task.list / decision.list / inbox.list — are side-effect-free and annotated read-only so hosts may auto-approve them. Write tools — connector.sync, propose.generate, propose.apply, task.create — ship today but stay behind human-in-the-loop approval (ADR-0004); nothing is applied or sent without your say.
bun run src/index.ts mcp serve # start the MCP server over stdio
Register it with an MCP host (Claude Code, Claude Desktop, Codex CLI, …). For Claude Desktop, add to claude_desktop_config.json:
{
"mcpServers": {
"suasor": {
"command": "suasor",
"args": ["mcp", "serve"]
}
}
}
Semantic search (recall.search) returns an embedding_disabled signal until you enable an embedding backend, so hosts gracefully fall back to FTS search (ADR-0005). See docs/design/mcp-surface.md for the tool schemas.
License
MIT
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