Agentmako

io.github.drhaltoPublished by GitHub account drhaltov0.2.3Updated Oct 24, 2026

Local-first codebase intelligence MCP server for AI coding agents.

Overview

AI-generated overview

Local-first codebase intelligence MCP server that indexes a repo so coding agents can ask evidence-backed questions about files, routes, symbols, diagnostics…

What you can do
  • Ask project questions across code, database facts, findings, diagnostics and literal checks, with help and status tools for orientation
  • Check changed-file impact, diagnostic freshness and completion gates before finishing an edit
  • Search the current disk with regex/glob inventories and run bounded lint diagnostics plus local rule-pack findings
  • Batch independent read-only follow-ups and discover specialized route, graph, DB or refresh tools on demand
  • Record and recall local database review comments and prior findings for repeated review work
When to use it
Useful when an AI coding agent needs to orient itself in an unfamiliar or large repository before editing, or when you want repeatable, evidence-backed answers about routes, symbols, conventions and schema instead of ad-hoc grep chains. Also fits staged review checks and Supabase/Postgres schema review.
Requirements
Runs as a local stdio process via the npm package agentmako; Node.js 20 or newer is required. The target project must first be attached and indexed with the agentmako CLI, and the MCP client config points at the agentmako mcp command. Optional Postgres/Supabase awareness needs a database URL, which can be supplied through an environment variable such as DATABASE_URL.
Before you install
Indexing and attaching a project writes local state and a SQLite store inside the project, and some tools are described as local-state mutations. Optional database setup stores secrets in the OS keychain by default, and interactive or scripted setup may read a database URL from DATABASE_URL; project config is said to store references rather than plaintext URLs. Database inspection is described as read-only, but review comments and findings are written locally.

Installation

In SourceWeft

  1. Open Agentmako in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

[agentmako logo]

agentmako

[npm version] [Smoke Tests] [License: Apache 2.0] [Node.js >=20] [agentmako MCP server]

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.

bash
npm install -g agentmako

Confirm the CLI is available:

bash
agentmako --versionagentmako 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:

bash
cd C:/path/to/your/project

Attach and index it:

bash
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

bash
agentmako status .agentmako tool list

Run a real Reef query:

bash
agentmako --json tool call . reef_ask "{\"question\":\"where should I inspect auth route state?\"}"

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:

bash
agentmako --json tool call . project_conventions "{}"

3. Configure your MCP client

Add this to your MCP client config:

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

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 watcher/schema health
  • reef_verify for the completion gate over diagnostic freshness and open loops
  • reef_impact for changed-file blast radius and convention risks
  • mako_help for an ordered workflow recipe with prefilled arguments
  • live_text_search for exact current-disk regex/glob inventories
  • lint_files for bounded diagnostics and .mako/rules findings
  • tool_batch for independent read-only follow-ups
  • tool_search to discover specialized route, graph, DB, finding, refresh, or context-expansion tools only when the compact surface points at a concrete need

4. Optional: use an agent plugin

Plain MCP works anywhere, but the bundled plugins add Mako-specific skills and include the same agentmako mcp wiring.

Prerequisites:

  • Claude Code installed
  • Node.js 20+ on PATH (the plugin runs npx -y agentmako mcp, which fetches the published agentmako package automatically — no separate global install required)
  • Your target project already attached with agentmako connect

Claude Code stable path:

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

New generated plugin layouts:

bash
claude plugin validate ./plugins/claude-codecodex marketplace add ./pluginsln -s "$(pwd)/plugins/cursor" ~/.cursor/plugins/local/mako-aigemini extensions install ./plugins/gemini

Inside the agent, confirm the mako-ai MCP server 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:

bash
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:

bash
agentmako connect .

For CI or scripted setup using an environment variable:

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

Then refresh and verify the local schema snapshot:

bash
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:

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

For staged review checks:

bash
agentmako git precommit . --json

For database review notes:

bash
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)
bash
git clone https://github.com/drhalto/agentmako.gitcd agentmakocorepack pnpm installcorepack pnpm run buildnpm 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

bash
corepack pnpm run typecheckcorepack pnpm run buildcorepack pnpm run test:smoke:reef-toolingcorepack pnpm run test:smoke:reef-model-facing-views

Full verification:

bash
corepack pnpm test

Repository Layout

text
apps/  cli/              agentmako CLI and MCP entrypoint (the published package)  web/              local dashboardpackages/  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 catalogservices/  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 workerextensions/         provider and integration packagesstorage/            schema migrations, models, queriestest/smoke/         smoke coveragemako-ai-claude-plugin/ Claude Code plugin with Mako skills

More Docs

License

Apache-2.0. See LICENSE.

Source: README.md at commit e0aaf38

Tools

0
SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

1
  1. v0.2.3LatestSep 16, 2026

Score

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