Agentmako

io.github.drhalto由 GitHub 帳號 drhalto 發布v0.2.3更新於 Oct 24, 2026

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

概覽

AI 產生的概覽

本地優先的程式碼庫智慧 MCP 伺服器,為儲存庫建立索引,讓編碼助理能就檔案、路由、符號、診斷與資料庫結構提出有證據支撐的問題。

可以做什麼
  • 跨程式碼、資料庫事實、發現、診斷與字面檢查回答專案問題,並提供說明與狀態工具引導流程
  • 檢查變更檔案的影響範圍、診斷新鮮度與完成前檢查
  • 以正規表示式/萬用字元清單搜尋目前磁碟內容,並執行有界 lint 診斷與本機規則包發現
  • 批次執行彼此獨立的唯讀後續查詢,按需探索路由、圖形、資料庫或重新整理等專用工具
  • 記錄並召回本機資料庫審查評論與既有發現,支援反覆審查工作
適用情境
適合 AI 編碼助理在修改前熟悉陌生或大型儲存庫,或需要關於路由、符號、慣例與資料庫結構的可重現、有證據的答案,而非臨時拼湊的 grep 鏈。也適用於暫存區審查檢查與 Supabase/Postgres 結構審查。
執行需求
透過 npm 套件 agentmako 以本機 stdio 程序執行,需要 Node.js 20 或更新版本。目標專案須先用 agentmako 命令列工具連接並建立索引,MCP 用戶端設定指向 agentmako mcp 命令。選用的 Postgres/Supabase 支援需要資料庫連線位址,可透過 DATABASE_URL 等環境變數提供。
安裝前請注意
連接與索引專案會在專案內寫入本機狀態與 SQLite 儲存,部分工具被標示為本機狀態變更。選用的資料庫設定預設把密鑰存入作業系統鑰匙圈,互動式或腳本化設定可能從 DATABASE_URL 讀取資料庫位址;專案設定據稱只儲存參照而非明文位址。資料庫檢查被描述為唯讀,但審查評論與發現會寫入本機。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Agentmako,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

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.

來源:README.md,提交 e0aaf38

工具

0
SourceWeft 尚未在沙箱中啟動過該軟體包,因此其工具未知。

版本歷史

1
  1. v0.2.3最新Sep 16, 2026

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