MCP 服务器

agentmako

Local-first codebase intelligence engine providing AI coding agents with a typed MCP toolset for understanding and navigating code repositories.

README

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 typed MCP toolset for understanding a project before they edit it. Mako indexes your repo, builds local SQLite-backed facts, tracks diagnostics and review notes, and returns structured context packets instead of making the agent 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
Deterministic context packets: context_packet, reef_scout
Code search and structure tools: cross_search, live_text_search, ast_find_pattern, repo_map
Reef Engine facts and findings across indexed, working-tree, and staged state
TypeScript, ESLint, Oxlint, Biome, and staged git diagnostic ingestion
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.

npm install -g agentmako

Confirm the CLI is available:

agentmako doctor

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:

cd C:/path/to/your/project

Attach and index it:

agentmako connect . --no-db

Use --no-db for the first run. It gets the code intelligence path working before adding database scope.

2. Confirm Mako sees the project

agentmako status .
agentmako tool list

Run a real scout query:

agentmako --json tool call . reef_scout "{\"query\":\"where should I inspect auth route state?\"}"

If that returns ranked candidates, facts, or findings, the core setup is working.

3. Configure your MCP client

Add this to your MCP client config:

{
  "mcpServers": {
    "mako-ai": {
      "command": "agentmako",
      "args": ["mcp"]
    }
  }
}

Restart the MCP client and confirm the mako-ai server starts.

In the agent, start with one of these tools:

tool_search when you need to find the right Mako tool
context_packet when you have a coding task and want starting context
reef_scout when you want ranked project facts/findings/history
ask when you have a natural-language repo question

4. Optional: use the Claude Code plugin

Plain MCP works with Claude Code, but the bundled plugin adds Mako-specific Claude skills and includes the same agentmako mcp wiring in mako-ai-claude-plugin/.mcp.json.

Prerequisites:

Claude Code installed
agentmako available on PATH
Your target project already attached with agentmako connect

From the agentmako repo root:

claude plugin validate .\mako-ai-claude-plugin
claude --plugin-dir .\mako-ai-claude-plugin

Inside Claude Code, run /mcp and confirm mako-ai is connected.

The plugin exposes these skills:

/mako-ai:mako-guide
/mako-ai:mako-discovery
/mako-ai:mako-trace
/mako-ai:mako-neighborhoods
/mako-ai:mako-graph
/mako-ai:mako-database
/mako-ai:mako-code-intel
/mako-ai:mako-workflow

Use the plugin when you want Claude Code to load Mako-specific guidance for which tools to call and how to interpret their results.

5. Optional: launch the dashboard

From your target project:

agentmako dashboard .

This starts the local API, harness service, and web dashboard.

6. Optional: add Supabase/Postgres awareness

Mako works without a database. Add this only after code intelligence is working.

For a one-time interactive setup:

agentmako connect .

For CI or scripted setup using an environment variable:

set DATABASE_URL=postgres://...
agentmako connect . --db-env DATABASE_URL --yes

Then refresh and verify the local schema snapshot:

agentmako refresh .
agentmako verify .

Interactive mode stores database secrets in your OS keychain by default. Project config stores references, not plaintext DB URLs.

Normal Daily Loop

From the target project:

agentmako status .
agentmako dashboard .
agentmako --json tool call . context_packet "{\"query\":\"fix the broken auth callback route\"}"

For staged review checks:

agentmako git precommit . --json

For database review notes:

agentmako --json tool call . db_review_comment "{\"objectType\":\"replication\",\"objectName\":\"supabase_database_replication\",\"category\":\"review\",\"comment\":\"Check publication coverage before relying on realtime events.\",\"tags\":[\"supabase\",\"replication\"]}"

Develop From Source

If you want to hack on Mako itself, clone and build instead of installing from npm.

Prerequisites:

Node.js 20 or newer
Git
Corepack (corepack enable, included with modern Node.js)

git clone https://github.com/drhalto/agentmako.git
cd agentmako
corepack pnpm install
corepack pnpm run build
npm link ./apps/cli

npm link ./apps/cli makes the source-built CLI available as agentmako on your PATH, replacing any global npm install. Re-run corepack pnpm run build after pulling changes.

To go back to the published version: npm install -g agentmako.

Development Checks

corepack pnpm run typecheck
corepack pnpm run build
corepack pnpm run test:smoke:reef-tooling
corepack pnpm run test:smoke:reef-model-facing-views

Full verification:

corepack pnpm test

Repository Layout

apps/
  cli/              agentmako CLI and MCP entrypoint (the published package)
  web/              local dashboard
packages/
  contracts/        public TypeScript contracts and tool schemas
  config/           shared config helpers
  logger/           shared logger
  sdk/              programmatic SDK
  store/            SQLite stores, migrations, and query helpers
  tools/            shared tool implementations
  harness-core/     local agent harness runtime
  harness-tools/    action tools available to the harness
  harness-contracts/ harness contracts and provider catalog
services/
  api/              local API and MCP transports
  engine/           Reef Engine fact/finding pipeline
  harness/          local harness HTTP service
  indexer/          repo and schema indexing logic
  worker/           background worker
extensions/         provider and integration packages
storage/            schema migrations, models, queries
test/smoke/         smoke coverage
mako-ai-claude-plugin/ Claude Code plugin with Mako skills