
Agentmako
io.github.drhaltoPublished by GitHub account drhaltov0.2.3Updated Oct 24, 2026
Local-first codebase intelligence MCP server for AI coding agents.
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.
Installation
In SourceWeft
- Open Agentmako in the dashboard and add it to a workspace.
- 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
[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_askacross code, database, findings, diagnostics, instructions, freshness, and literal checks - Queryable workflow orientation:
mako_help - Deterministic context expansion:
context_packet _hintson 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, andtool_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/rulesYAML rule packs, including primitive cross-file helper-bypass rules viacanonicalHelper - 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_askfor project questions across code, database, findings, diagnostics, freshness, and quoted literal checksreef_statusfor maintained issues, changed files, stale diagnostics, and watcher/schema healthreef_verifyfor the completion gate over diagnostic freshness and open loopsreef_impactfor changed-file blast radius and convention risksmako_helpfor an ordered workflow recipe with prefilled argumentslive_text_searchfor exact current-disk regex/glob inventorieslint_filesfor bounded diagnostics and.mako/rulesfindingstool_batchfor independent read-only follow-upstool_searchto 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 runsnpx -y agentmako mcp, which fetches the publishedagentmakopackage automatically — no separate global install required) - Your target project already attached with
agentmako connect
Claude Code stable path:
New generated plugin layouts:
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:
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:
For CI or scripted setup using an environment variable:
Then refresh and verify the local schema snapshot:
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:
For staged review checks:
For database review notes:
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)
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
Full verification:
Repository Layout
More Docs
- Tool overview
- CLI docs
- Reef Engine
- Tool annotations
- Write tool convention
- Claude Code plugin
- Agent guidance to paste into CLAUDE.md / AGENTS.md
- Contributing
- Security policy
- Changelog
License
Apache-2.0. See LICENSE.
Source: README.md at commit e0aaf38
Tools
0Version history
1- v0.2.3LatestSep 16, 2026
Score
50% of the applicable checks met
How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.
- Reached in the last 30 days25 pts
Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.
- Auth declared10 pts
Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.
- Tools listed15 pts
Answer tools/list without a credential, or ship a package that starts in a sandbox without one.
- DescriptionRequired15 pts
- Logo10 pts
- Documentation15 pts
- License10 pts