Agentmako

io.github.drhalto由 GitHub 账号 drhalto 发布v0.2.3更新于 Oct 24, 2026

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

概览

AI 生成的概览

本地优先的代码库智能 MCP 服务器,为仓库建立索引,让编码助手能就文件、路由、符号、诊断和数据库结构提出有证据支撑的问题。

可以做什么
  • 跨代码、数据库事实、发现、诊断和字面量检查回答项目问题,并提供帮助与状态工具做流程引导
  • 检查改动文件的影响范围、诊断新鲜度和完成前检查
  • 以正则/通配清单搜索当前磁盘内容,并运行有界 lint 诊断与本地规则包发现
  • 批量执行相互独立的只读后续查询,按需发现路由、图、数据库或刷新等专用工具
  • 记录并召回本地数据库评审评论与既往发现,支持重复评审工作
适用场景
适合 AI 编码助手在修改前熟悉陌生或大型仓库,或需要关于路由、符号、约定和数据库结构的可重复、有证据的答案,而不是临时拼凑的 grep 链。也适用于暂存区评审检查和 Supabase/Postgres 结构评审。
运行要求
通过 npm 包 agentmako 以本地 stdio 进程运行,需要 Node.js 20 或更高版本。目标项目须先用 agentmako 命令行工具连接并建立索引,MCP 客户端配置指向 agentmako mcp 命令。可选的 Postgres/Supabase 支持需要数据库连接地址,可通过 DATABASE_URL 等环境变量提供。
安装前请注意
连接和索引项目会在项目内写入本地状态和 SQLite 存储,部分工具被标注为本地状态变更。可选的数据库配置默认把密钥存入操作系统钥匙串,交互式或脚本化配置可能从 DATABASE_URL 读取数据库地址;项目配置据称只保存引用而非明文地址。数据库检查被描述为只读,但评审评论和发现会写入本地。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Agentmako,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照 仓库 中的启动说明。

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.

来源:README.md,提交 e0aaf38

工具

0
SourceWeft 尚未在沙箱中启动过该软件包,因此其工具未知。

版本历史

1
  1. v0.2.3最新Sep 16, 2026

评分

已满足适用检查项的 50%

该评分衡量此收录条目的完整程度,依据注册中心条目、端点与公开来源计算得出。它不是对服务器本身的评价,也不表示服务器安全或当前可用:可连通性是带日期的检查结果,评分也不包含安装量或用户评价。

  • 近 30 天内可连通25 分

    请保持端点能够响应 MCP 握手;SourceWeft 每 30 天探测一次。

  • 已声明认证方式10 分

    请在注册中心条目中声明凭据请求头,或保持端点能够响应探测,以便判定其认证方式。

  • 已列出工具15 分

    请让服务器在无凭据时响应 tools/list,或发布可在沙箱中无凭据启动的软件包。

  • 描述必需15 分
  • 图标10 分
  • 文档15 分
  • 许可证10 分