原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
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Agentmako

作者:drhalto版本 0.2.3i★ –i在你的电脑上运行
注册名称io.github.drhalto/agentmako

安装

概览

作者提供的说明(英文原文)

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

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 开发者工具

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 注册中心没有列出需要填写的密钥。

你需要

  • npm已安装 Node.js(用于 npx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "agentmako": {
      "command": "npx",
      "args": [
        "-y",
        "agentmako"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add agentmako -- npx -y agentmako

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "agentmako": {
      "command": "npx",
      "args": [
        "-y",
        "agentmako"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "agentmako": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "agentmako"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 drhalto 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“开发者工具”中的其他服务器比较i

  • 星标数多于此分类中其他 1392 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 1392 个服务器的 16% 更新
  • 基础检查结果等于或优于此分类中其他 1392 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Agentmako 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.2.3)于6个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。

有什么可以替代它?

同一分类中有:GitHub, Desktop Commander, Cloudflare MCP

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

GitHub

作者:github

Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.

电脑或云端★ 34,245MIT3天前更新
安装

Desktop Commander

作者:wonderwhy-er

MCP server for terminal commands, file operations, and process management

在你的电脑上运行★ 10,225MIT15天前更新
安装

Cloudflare MCP

作者:cloudflare

Cloudflare MCP servers

在云端运行★ 4,446Apache-2.014个月前更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

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 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.

npm install -g agentmako

Confirm the CLI is available:

agentmako --version

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 Reef query:

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:

agentmako --json tool call . project_conventions "{}"
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, 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:

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

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

New generated plugin layouts:

claude plugin validate ./plugins/claude-code

codex marketplace add ./plugins ln -s "$(pwd)/plugins/cursor" ~/.cursor/plugins/local/mako-ai gemini 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:

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

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.

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