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)
AI code research platform. Search, analyze, and extract insights from any GitHub repository.
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。
GITHUB_TOKEN标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。
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": {
"octocode": {
"command": "npx",
"args": [
"-y",
"octocode-mcp"
],
"env": {
"GITHUB_TOKEN": "your-value"
}
}
}
}在终端中运行这条命令
claude mcp add octocode --env GITHUB_TOKEN=your-value -- npx -y octocode-mcp运行前请先填写空着的值。
粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"octocode": {
"command": "npx",
"args": [
"-y",
"octocode-mcp"
],
"env": {
"GITHUB_TOKEN": "your-value"
}
}
}
}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": {
"octocode": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"octocode-mcp"
],
"env": {
"GITHUB_TOKEN": "your-value"
}
}
}
}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7日
注册名称已通过 GitHub 账户 bgauryy 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。
你需要填写:GITHUB_TOKEN
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(7.0.9)于12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。
Evidence-first code research for AI agents and developers.
Octocode researches your local code and external code alike (GitHub repositories, PRs, npm) with one toolset: ripgrep + AST search, trees, precise reads, and LSP. Use it as a CLI or MCP server, backed by a Rust engine for fast, token-efficient results across single files or mega-repos.
Prerequisites: Node.js 20.12+
1. Run the Octocode CLI with `npx`
npx octocode --help
2. Authenticate with GitHub - optional, but unlocks private repositories and higher API rate limits:
npx octocode auth login
npx octocode status # verify the active token source
3. Choose your interface. Same tools and Rust engine on both. (Clone is on by default in the CLI, opt-in for MCP.)
🖥️ CLI - research straight from your terminal:
npx octocode
🤖 MCP - one-click install:
Show more install options (Windsurf, Kiro, Goose, LM Studio, Claude Code)
Claude Code:
claude mcp add-json octocode --scope user '{"command":"npx","type":"stdio","args":["octocode-mcp@latest"]}'
Any other client: npx octocode install
Add to your MCP client config (or use a one-click install above):
{
"octocode": { "command": "npx", "type": "stdio", "args": ["octocode-mcp@latest"] } }
Put a GitHub token and options under env (see Configuration).
Run npx octocode and agents figure out the rest. The bare command prints built-in usage and the full tool catalog, so any coding agent knows how to drive it out of the box, no MCP client or extra wiring required.
npx octocode # self-describing usage for agents
npx octocode tools # list every tool npx octocode tools localSearchCode --scheme # inspect a tool's schema
Every MCP tool is also a plain command: JSON in, token-efficient YAML out. Local paths route to local tools; owner/repo[/path] routes to GitHub.
npx octocode tools localSearchCode \
--queries '{"path":".","searchText":"authenticate","maxFiles":20}'
```yaml
results:
Learn more at [octocode.ai](https://octocode.ai).
Agents code better from evidence than from guesses. Octocode researches two worlds with one flow, your local code and external code on GitHub and npm, and hands back compact, citable context before an agent changes, reviews, or explains code. *Code is truth; context is the map.*
Most tools do one slice (web search, or grep your repository) and hand back a fixed blob. Octocode covers the whole loop and lets the agent decide what data it needs next:
What you can do (whenever the next step needs proven context, not a guess):
| Need | Use Octocode to |
|---|---|
| Codebase questions | Search local or GitHub code, read exact regions, browse trees, and carry file/line anchors into the answer. |
| Implementation research | Compare patterns across repositories, npm packages, pull requests, commits, and local files before changing code. |
| Semantic navigation | Resolve definitions, references, callers/callees, call hierarchy, hovers, symbols, diagnostics, and type relationships through LSP. |
| Structural matching | Run AST-shaped searches with patterns or YAML rules so comments and strings do not become false positives. |
| Large-file context | Minify, skeletonize, or paginate code so agents spend tokens on relevant structure instead of boilerplate. |
| Agent workflows | Same engine through MCP, CLI, and Agent Skills. |
A blind, head-to-head test on research-oriented flows rather than plain lookups (multi-hop traces, dependency/call-graph chains, commit ranges, blast-radius, PR reviews across repositories).
How it works: 30 GitHub questions × 3 passes; Octocode vs gh, gh+Headroom, and gh+RTK on identical questions (only the CLI differs). A blind judge (gpt-5.5) grades correctness; the metric is characters through the model, counted from instrumented logs (characters, not tokens). Result: at near-parity correctness, Octocode answers with ~2.0× fewer characters than plain `gh`, ~2.6× fewer than `gh`+Headroom, and ~3.2× fewer than `gh`+RTK in the local-build headline runs.
▶ [Open the interactive report](https://raw.githack.com/bgauryy/octocode/main/packages/octocode-benchmark/results/index.html) · [run it / method](https://github.com/bgauryy/octocode/tree/main/packages/octocode-benchmark/skills/octocode-benchmark) · questions · all reports
17 tools in the full catalog. How many register depends on the surface and the flags you set:
| Surface | Registers | What that set is |
|---|---|---|
| MCP, no flags | 8 | GitHub search and read, plus npmSearch |
MCP, ENABLE_LOCAL=true | 14 | Adds the five local tools and lspGetSemantics |
MCP, + ENABLE_CLONE=true | 15 | Adds ghCloneRepo |
MCP, + ENABLE_TOOLS allowlist | 17 | Adds ghListReleases and ghSearchDiscussions |
| CLI, no flags | 15 | Local tools and clone are on by default |
CLI, + ENABLE_RELEASES=1 ENABLE_DISCUSSIONS=1 | 17 | Adds the same two GitHub tools |
ghListReleases and ghSearchDiscussions need two settings on MCP, not one: ENABLE_RELEASES=1 or ENABLE_DISCUSSIONS=1 puts the tool in the catalog, and ENABLE_TOOLS="ghListReleases,ghSearchDiscussions" registers it. Either setting alone leaves the tool unregistered, because both carry isDefault: false and the MCP registration filter admits only default or explicitly allowlisted tools. The CLI needs only the ENABLE_RELEASES and ENABLE_DISCUSSIONS flags. ENABLE_LOCAL and ENABLE_CLONE accept true or 1; ENABLE_RELEASES and ENABLE_DISCUSSIONS also accept yes and on. Flags: Configuration.
Token knobs. concise:true returns path/title-only lists. minify controls file read density: symbols = skeleton with line numbers, standard = comments/blanks stripped (default), none = exact bytes.
| Tool | What it does | Knob |
|---|---|---|
ghSearchCode | Code and path search across GitHub by owner, repository, path, filename, extension, and match filters. Accepts 1 to 5 parallel queries. | concise |
ghGetFileContent | Read a GitHub file or region: full file, line range, match slice, or paginated chars. |
只显示了开头部分;其余内容请在仓库中阅读