GitHub MCP Server
/install github-mcp
GitHub MCP Server
Complete GitHub Integration for AI Agents
Connect AI agents to GitHub for repository management, code operations, issue tracking, pull requests, and the full GitHub API.
Why GitHub MCP?
🤖 Agent-Native GitHub Workflows
Enable agents to perform complex GitHub operations that previously required manual API integration:
- Clone and navigate repositories
- Read and modify files
- Create issues and pull requests
- Review code and discussions
- Manage branches and releases
🔐 Secure Authentication
OAuth-based authentication with fine-grained permissions. Agents access only what you authorize.
📦 Zero Setup for Common Operations
Pre-configured tools for the most common GitHub workflows. No manual API calls required.
Installation
Option 1: Official MCP Server (Archived - Community Maintained)
# Community-maintained GitHub MCP server
npm install -g @modelcontextprotocol/server-github
# Or build from source
git clone https://github.com/modelcontextprotocol/servers-archived
cd servers-archived/src/github
npm install
npm run build
Option 2: Third-Party Implementations
Several community implementations available. Check the MCP Registry for current options.
Configuration
Add to your MCP client config:
{
"mcpServers": {
"github": {
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-github"],
"env": {
"GITHUB_PERSONAL_ACCESS_TOKEN": "ghp_your_token_here"
}
}
}
}
Get GitHub Token
- Go to https://github.com/settings/tokens
- Generate new token (classic) or fine-grained token
- Select scopes:
repo- Full repository accessread:user- Read user profileread:org- Read organization data (if needed)
Fine-Grained Token (recommended):
- Repository permissions: Contents (Read/Write), Issues (Read/Write), Pull Requests (Read/Write)
- Organization permissions: Members (Read) if accessing org repos
Available Tools
Repository Operations
1. Create Repository
Agent: "Create a new repository called 'my-project'"
2. Clone Repository
Agent: "Clone the OpenAI GPT-4 repository"
3. List Repository Files
Agent: "What files are in the src/ directory?"
File Operations
4. Read File
Agent: "Show me the README.md file"
Agent: "Read the contents of src/index.ts"
5. Create/Update File
Agent: "Create a new file docs/API.md with API documentation"
Agent: "Update the version in package.json to 2.0.0"
6. Search Code
Agent: "Search for files containing 'authentication logic'"
Agent: "Find where the DatabaseConnection class is defined"
Issue & PR Management
7. Create Issue
Agent: "Create an issue: 'Add dark mode support'"
8. List Issues
Agent: "Show me all open bugs"
Agent: "What issues are assigned to me?"
9. Create Pull Request
Agent: "Create a PR to merge feature/login into main"
10. Review Pull Request
Agent: "Review PR #42 and check for security issues"
Branch Operations
11. Create Branch
Agent: "Create a new branch called 'feature/user-auth'"
12. List Branches
Agent: "Show all branches in this repo"
13. Merge Branch
Agent: "Merge 'develop' into 'main'"
Advanced Operations
14. Create Release
Agent: "Create a release v2.0.0 with the latest changes"
15. Search Repositories
Agent: "Find popular React component libraries"
16. Fork Repository
Agent: "Fork the Vue.js repository to my account"
Agent Workflow Examples
Code Review Automation
Human: "Review all PRs and flag security issues"
Agent:
1. list_pull_requests(state="open")
2. For each PR:
- get_pull_request(pr_number)
- read_changed_files()
- analyze for security vulnerabilities
- create_review_comment(security_findings)
Issue Triage
Human: "Label all new issues with 'needs-triage'"
Agent:
1. list_issues(state="open", labels=null)
2. For each unlabeled issue:
- read_issue(issue_number)
- add_label("needs-triage")
Release Automation
Human: "Prepare v2.0.0 release"
Agent:
1. create_branch("release/v2.0.0")
2. update_file("package.json", version="2.0.0")
3. update_file("CHANGELOG.md", new_release_notes)
4. create_pull_request("release/v2.0.0" -> "main")
5. create_release(tag="v2.0.0", notes=changelog)
Documentation Sync
Human: "Update documentation from code comments"
Agent:
1. search_code(query="* @description")
2. extract_docstrings()
3. generate_markdown_docs()
4. update_file("docs/API.md", generated_docs)
5. create_pull_request("Update API documentation")
Use Cases
🛠️ Development Assistants
Agents that help developers with repetitive GitHub tasks: creating issues, managing labels, updating documentation, code review.
🤖 CI/CD Automation
Build agents that trigger workflows, check build status, create releases, manage deployments.
📊 Repository Analytics
Analyze code quality, track issue resolution time, monitor PR velocity, generate reports.
🔍 Code Search & Discovery
Find code patterns, identify dependencies, discover similar implementations, locate technical debt.
📝 Documentation Automation
Sync code comments to docs, generate API references, update changelogs, maintain README files.
Security Best Practices
✅ Use Fine-Grained Tokens
Prefer fine-grained tokens over classic PATs. Limit scope to specific repositories and permissions.
✅ Read-Only When Possible
If the agent only needs to read code/issues, grant read-only access.
✅ Environment Variables
Never hard-code tokens. Always use environment variables.
✅ Token Rotation
Rotate tokens regularly. Set expiration dates.
✅ Audit Agent Actions
Monitor what the agent does. GitHub activity log tracks all API operations.
Rate Limits
Authenticated Requests:
- 5,000 requests/hour (per user)
- Search API: 30 requests/minute
Best Practices:
- Cache repository data when possible
- Batch operations where applicable
- Use conditional requests (
If-None-Matchheaders)
vs Manual GitHub API Integration
| Task | Manual API | GitHub MCP |
|---|---|---|
| Setup Time | Hours (auth, SDK, error handling) | Minutes (config file) |
| Code Required | Yes (HTTP client, auth, parsing) | No (MCP tools auto-discovered) |
| Agent Integration | Manual tool definitions | Automatic via MCP |
| Auth Management | Custom implementation | Built-in OAuth flow |
| Error Handling | Custom retry logic | Handled by server |
Troubleshooting
"Bad credentials" Error
- Verify token has not expired
- Ensure token has required scopes (
repo,read:user) - Check token is correctly set in environment variable
"Resource not found" Error
- Verify repository name format:
owner/repo - Check agent has access to private repositories (if applicable)
- Ensure branch/file path exists
Rate Limit Errors
- Wait for rate limit reset (check
X-RateLimit-Resetheader) - Reduce query frequency
- Consider GitHub Apps for higher limits
Resources
- MCP Registry: https://registry.modelcontextprotocol.io/
- GitHub API Docs: https://docs.github.com/en/rest
- Create Token: https://github.com/settings/tokens
- Rate Limits: https://docs.github.com/en/rest/overview/rate-limits-for-the-rest-api
Advanced Configuration
{
"mcpServers": {
"github": {
"command": "node",
"args": ["/path/to/github-mcp/build/index.js"],
"env": {
"GITHUB_PERSONAL_ACCESS_TOKEN": "ghp_xxx",
"GITHUB_API_URL": "https://api.github.com",
"DEFAULT_BRANCH": "main",
"AUTO_PAGINATION": "true"
}
}
}
}
The GitHub integration every coding agent needs: From code review to release automation, GitHub MCP brings the full power of GitHub to AI agents.
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install github-mcp - 安装完成后,直接呼叫该 Skill 的名称或使用
/github-mcp触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
GitHub MCP Server 是什么?
GitHub MCP Server enables AI agents to manage repos, read/update files, handle issues/PRs, branches, and automate GitHub workflows via the API. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 2086 次。
如何安装 GitHub MCP Server?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install github-mcp」即可一键安装,无需额外配置。
GitHub MCP Server 是免费的吗?
是的,GitHub MCP Server 完全免费(开源免费),可自由下载、安装和使用。
GitHub MCP Server 支持哪些平台?
GitHub MCP Server 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 GitHub MCP Server?
由 Siddharth Menon(@buddhasource)开发并维护,当前版本 v1.0.0。