mcp-pagerduty
A Model Context Protocol (MCP) server that provides integration with PagerDuty for incident management and monitoring operations.
Documentation
MCP PagerDuty
🚧 Early Development - Work in Progress 🚧
A Model Context Protocol (MCP) server that provides integration with PagerDuty for incident management and monitoring operations.
⚠️ Project Status
This project is in its initial development phase. Many features are planned but not yet implemented. Contributions and feedback are welcome!
🚀 Getting Started
Prerequisites
- Python 3.13 or higher
- PagerDuty API token
Installation
1. Clone the repository
git clone https://github.com/judexzhu/mcp-pagerduty.git
cd mcp-pagerduty2. Install dependencies with UV
uv sync3. Configure environment
cp .env.example .env
# Edit .env with your PagerDuty API credentialsConfiguration
Create a `.env` file with your PagerDuty configuration:
PAGERDUTY_API_TOKEN=your_api_token_here
PAGERDUTY_API_URL=https://api.pagerduty.comNote: `PAGERDUTY_API_URL` is optional and defaults to `https://api.pagerduty.com` if not specified.
🔧 Development
This project is actively under development. Current structure:
mcp-pagerduty/
├── pagerduty.py # Main MCP server implementation
├── pyproject.toml # Project configuration
├── .env # Environment variables (create from .env.example)
└── README.md # This fileRunning the Server
python pagerduty.py📚 MCP Integration
This server implements the Model Context Protocol to provide PagerDuty functionality to AI assistants and other MCP clients.
Current Tools
- `pagerduty_list_incidents` - List incidents with filtering options
- `pagerduty_get_incident` - Get detailed incident information
- `pagerduty_get_incident_notes` - Get detailed incident information
Planned Resources
- Incident templates
- Escalation policy information
- Service status dashboards
🤝 Contributing
This project is in early development and contributions are very welcome!
How to Contribute
1. Fork the repository
2. Create a feature branch
git checkout -b feature/your-feature-name3. Make your changes
4. Add tests (when testing framework is set up)
5. Submit a pull request
Development Priorities
Current development priorities:
1. 🔴 High Priority: Basic incident listing and retrieval
2. 🟡 Medium Priority: Incident creation and updates
3. 🟢 Low Priority: Advanced features like escalation management
📋 TODO
- [ ] Implement basic MCP server structure
- [ ] Add PagerDuty API client
- [ ] Implement incident management tools
- [ ] Add comprehensive error handling
- [ ] Write tests
- [ ] Add logging and monitoring
- [ ] Create example configurations
- [ ] Write comprehensive documentation
🐛 Known Issues
- Project is in initial development phase
- No functionality implemented yet
- API integration not yet built
📖 Resources
📄 License
This project is licensed under the MIT License - see the LICENSE file for details.
🆘 Support
Since this project is in early development:
- 📝 Documentation: Coming soon
- 🐛 Bug Reports: Please open an issue
- 💡 Feature Requests: Welcome via issues
- 💬 Questions: Open a discussion or issue
Note: This project is not affiliated with PagerDuty, Inc. It's a community-driven integration for the Model Context Protocol.
Frequently asked questions
What is mcp-pagerduty?
mcp-pagerduty is A Model Context Protocol (MCP) server that provides integration with PagerDuty for incident management and monitoring operations.
How do I install mcp-pagerduty?
Open the GitHub repository and follow its README. Most MCP servers are added to your client's MCP config, then called by your agent.
Is mcp-pagerduty open source?
Yes — it is hosted on GitHub at https://github.com/judexzhu/mcp-pagerduty.
Related MCP tools
🙌 OpenHands: Code Less, Make More for the Model Context Protocol. Enhance AI assistants with powerful integrations. Python-based implementation.
Universal memory layer for AI Agents; Announcing OpenMemory MCP - local and secure memory management. Python-based implementation.
基于大模型搭建的聊天机器人,同时支持 微信公众号、企业微信应用、飞书、钉钉 等接入,可选择ChatGPT/Claude/DeepSeek/文心一言/讯飞星火/通义千问/ Gemini/GLM-4/Kimi/LinkAI,能处理文本、语音和图片,访问操作系统和互联网,支持基于自有知识库进行定制企业智能客服。
An LLM agent that conducts deep research (local and web) on any given topic and generates a long report with citations. Built for the Model Context Protocol to
🚀 The fast, Pythonic way to build MCP servers and clients Trusted by 19900+ developers. Trusted by 19900+ developers. Trusted by 19900+ developers.
🔥 MaxKB is an open-source platform for building enterprise-grade agents. MaxKB 是强大易用的开源企业级智能体平台。 for the Model Context Protocol. Enhance AI assistants with po
Run your own MCP server? See who uses it and what to fix.
Measure it with TrackMCP