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

1. Go to https://github.com/settings/tokens
2. Generate new token (classic) or fine-grained token
3. Select scopes:

• repo - Full repository access
• read:user - Read user profile
• read: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-Match headers)

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-Reset header)
• 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"
      }
    }
  }
}

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The GitHub integration every coding agent needs: From code review to release automation, GitHub MCP brings the full power of GitHub to AI agents.