drhalto/agentmako

agentmako is a local-first codebase intelligence engine for AI coding
tools.
It gives agents like Codex, Claude Code, Cursor, and local harnesses a
compact Reef-first tool surface for understanding a project before they edit
it. Mako indexes your repo, builds local SQLite-backed facts, tracks
diagnostics and review notes, and answers evidence-backed questions instead of
making the agent orchestrate broad tool chains or rediscover everything with
raw grep.
Mako is built for the first mile of coding-agent work:
> What files matter? What routes, symbols, tables, diagnostics, and prior
> findings are relevant? What should the agent read next?
What You Get
- MCP server for coding agents: agentmako mcp
- Local dashboard: agentmako dashboard
- Primary project query: reef_ask across code, database, findings,
diagnostics, instructions, freshness, and literal checks
- Queryable workflow orientation: mako_help
- Deterministic context expansion: context_packet
- _hints on tool results so agents get result-specific next steps
- Central MCP annotations so clients can distinguish safe reads, live reads,
and local-state mutations
- Compact loop/fallback tools: reef_status, reef_verify, reef_impact,
live_text_search, lint_files, and tool_batch
- Reef Engine facts and findings across indexed,
working-tree, and staged state
- Reef convention extraction for auth guards, runtime boundaries, generated
paths, route patterns, and schema usage
- TypeScript, ESLint, Oxlint, Biome, and staged git diagnostic ingestion
- Hot-reloaded .mako/rules YAML rule packs, including primitive
cross-file helper-bypass rules via canonicalHelper
- Optional Postgres/Supabase schema snapshots and read-only DB inspection
- Local DB review comments for notes on tables, RLS, triggers,
publications, subscriptions, and replication
- Recall, acknowledgements, and agent feedback for repeated review work
Everything important runs locally. No hosted service is required.
Install
Requires **Node.js 20 or newer**.
Confirm the CLI is available:
You should see green checks for configuration and the local API service.
> Prefer to build from source (e.g. to contribute)? See
> Develop From Source at the bottom of this
> file.
Happy Path Setup
1. Attach your real project
Go to the project you want Mako to understand:
Attach and index it:
Use --no-db for the first run. It gets the code intelligence path
working before adding database scope.
2. Confirm Mako sees the project
Run a real Reef query:
If that returns an evidence-backed answer, facts, findings, or next queries,
the core setup is working.
reef_ask plans over code, database, durable findings, diagnostics, and exact
literal evidence. App-flow questions favor file, route, and finding evidence;
RLS/schema questions favor database facts and review comments. To inspect
project rules of thumb directly:
3. Configure your MCP client
Add this to your MCP client config:
Restart the MCP client and confirm the mako-ai server starts.
In the agent, default to reef_ask. The compact starting surface is:
- reef_ask for project questions across code, database, findings,
diagnostics, freshness, and quoted literal checks
- reef_status for maintained issues, changed files, stale diagnostics, and