GitHub
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
作者提供的说明(英文原文)
Local-first codebase intelligence MCP server for AI coding agents.
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。
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。
选择你使用的 AI 应用,然后复制设置。
你需要
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。
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。
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
注册名称已通过 GitHub 账户 drhalto 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
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。
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。
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)。
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。
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。
同一分类中有:GitHub, Desktop Commander, Cloudflare MCP
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
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
MCP server for terminal commands, file operations, and process management
Cloudflare MCP servers
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 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?
agentmako mcpagentmako dashboardreef_ask across code, database, findings, diagnostics, instructions, freshness, and literal checksmako_helpcontext_packet_hints on tool results so agents get result-specific next stepsreef_status, reef_verify, reef_impact, live_text_search, lint_files, and tool_batch.mako/rules YAML rule packs, including primitive cross-file helper-bypass rules via canonicalHelperEverything important runs locally. No hosted service is required.
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.
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.
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 "{}"
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 checksreef_status for maintained issues, changed files, stale diagnostics, and watcher/schema healthreef_verify for the completion gate over diagnostic freshness and open loopsreef_impact for changed-file blast radius and convention risksmako_help for an ordered workflow recipe with prefilled argumentslive_text_search for exact current-disk regex/glob inventorieslint_files for bounded diagnostics and .mako/rules findingstool_batch for independent read-only follow-upstool_search to discover specialized route, graph, DB, finding, refresh, or context-expansion tools only when the compact surface points at a concrete needPlain MCP works anywhere, but the bundled plugins add Mako-specific skills and include the same agentmako mcp wiring.
Prerequisites:
PATH (the plugin runs npx -y agentmako mcp, which fetches the published agentmako package automatically — no separate global install required)agentmako connectClaude 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-workflowUse the plugin when you want Claude Code to load Mako-specific guidance for which tools to call and how to interpret their results.
From your target project:
agentmako dashboard .
This starts the local API, harness service, and web dashboard.
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.
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\"]}"
If you want to hack on Mako itself, clone and build instead of installing from npm.
Prerequisites:
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.
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
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
Apache-2.0. See LICENSE.