Raygun MCP Server: Enabling Seamless Integration for AI Applications

Overview: What is Raygun MCP Server?

The Raygun MCP Server acts as a critical link between Raygun's robust suite of developer tools—specifically its APIs for Crash Reporting and Real User Monitoring—and the broader ecosystem of Model Context Protocol (MCP) clients. This server translates complex interactions into standardized, high-level commands through MCP, making it easier for AI applications like Claude Desktop, Continue, Cursor, and others to efficiently leverage Raygun's vast data resources in a structured manner.

🔧 Core Features & MCP Capabilities

The Raygun MCP Server provides comprehensive API access using the Model Context Protocol. This protocol offers a unified interface that simplifies integration without requiring significant changes or adaptations from the AI applications side. By utilizing the server, developers can seamlessly access Raygun's extensive feature set, including error management tools, deployment tracking, source maps, and user session data.

Applications

• List Application: Retrieve a list of all applications associated with your account.
• Get Application: Obtain detailed information about an application based on its identifier or API key.
• Regenerate Application API Key: Generate a new API key for an existing application to ensure security and manage access control effectively.

Error Management

• List Error Groups: Identify groups of related errors based on specific criteria like frequency, users affected, etc.
• Get Error Group: Gain detailed insights into the issues flagged by Raygun’s error monitoring tools.
• Resolve/Activate/Ignorer Permanently Ignore Error Group: Set the status of a particular error to resolved, active, or ignored depending on your needs.

Deployment Management

• List Deployments: Track all deployments associated with an application for better change management and rollbacks.
• Get Update/Delete/Reprocess Deployment Commit: Retrieve, modify, or remove specific deployment data to maintain accurate records and ensure traceability.

User & Session Management

• List Customers/Sessions: Access customer details and user sessions to analyze usage patterns and identify issues proactively.
• Get Detailed Session Information: Fetch granular session data essential for advanced analytics and troubleshooting endpoints.

Performance Monitoring

• List Monitored Pages/Metrics: Track key performance indicators across monitored pages, providing real-time insight into application health.
• Source Maps Management: Handle source maps to debug errors more effectively by mapping stack traces to line numbers in the codebase.

Team Management

• Invitations/Permissions Management: Set up and manage team invitations to ensure smooth collaboration amongst different stakeholders.

⚙️ MCP Architecture & Protocol Implementation

The MCP protocol flow ensures that data requests from AI applications are efficiently processed and responded to via standardized commands, making it accessible for both developers and end users. The architecture leverages a combination of environment variables and command-line execution to establish connections between the client and server securely.

graph TD
    A[AI Application] -->|MCP Client| B[MCP Protocol]
    B --> C[MCP Server]
    C --> D[Data Source/Tool]
    style A fill:#e1f5fe
    style C fill:#f3e5f5
    style D fill:#e8f5e8

This diagram illustrates the flow of commands from an AI application client (Claude Desktop, Continue, Cursor) through MCP to the Raygun MCP Server for processing and onward transmission to relevant data sources/tools.

🚀 Getting Started with Installation

To integrate the Raygun MCP Server into your development environment, follow these steps:

1. Environment Setup: Ensure that you have Node.js installed on your system.
2. Install Dependencies: Run npm install in the project directory to set up necessary dependencies.
3. Configure Environment Variables: Use the following environment variables:

   {
     "RAYGUN_PUBLIC_TOKEN": "your-pat-token-here"
   }
   

💡 Key Use Cases in AI Workflows

Developers can use this MCP server integration to enhance their AI workflows by providing real-time insights into error groups, user sessions, and other critical data points. Here are two practical examples:

Error Management

By integrating Raygun's error management tools via the MCP protocol, developers can quickly resolve issues with minimal manual intervention. For instance, a prompt could be provided within an AI application like Continue to automatically send all unresolvable errors from Raygun into an integrated bug tracking system.

{
  "mcpServers": {
    "raygun": {
      "command": "npx",
      "args": ["-y", "@raygun.io/mcp-server-raygun"],
      "env": {
        "RAYGUN_PUBLIC_TOKEN": "your-pat-token-here"
      }
    }
  }
}

Source Maps Management

AI applications like Cursor can use the MCP server to handle source maps more effectively, streamlining the process of debugging complex errors. This results in faster resolution times and improved user experience.

🔌 Integration with MCP Clients

The Raygun MCP Server is designed to work seamlessly with all MCP clients, including Claude Desktop, Continue, and Cursor. The compatibility matrix below shows full support for all relevant features:

MCP Client	Resources	Tools	Prompts	Status
Claude Desktop	✅	✅	✅	Full Support
Continue	✅	✅	✅	Full Support
Cursor	❌	✅	❌	Tools Only

📊 Performance & Compatibility Matrix

The Raygun MCP Server has been rigorously tested and optimized for performance, ensuring that data requests are handled in the shortest time possible. The compatibility matrix below showcases the supported features across different environments:

Environment	List Applications	Get Application	Regenerate API Key
MacOS	✅	✅	✅
Linux	✅	✅	✅
Windows	✅	✅	✅

🛠️ Advanced Configuration & Security

For advanced users and enterprises, the server offers extensive configuration options to customize behavior and ensure data security. Environment variables such as SOURCEMAP_ALLOWED_DIRS can be used to define directories where source maps are allowed.

{
  "env": {
    "SOURCEMAP_ALLOWED_DIRS": "/path/to/allowed/directories"
  }
}

❓ Frequently Asked Questions (FAQ)

Q1: How do I troubleshoot issues with the Raygun MCP Server?

To diagnose problems, first ensure all environment variables are correctly set. Additionally, you can use the MCP Inspector to debug and inspect the flow of commands between your AI application and the Raygun server.

npm run inspector

Q2: Can I use this server with other Raygun products beyond Crash Reporting?

Yes, while primarily designed for Crash Reporting and RUM, this MCP server can be adapted or extended through custom configuration to support additional Raygun products and services as needed.

Q3: Are there any limitations on the API rate limits with Raygun via the MCP Server?

Raygun imposes certain rate limits based on usage patterns. Check the official documentation for detailed guidelines and consider implementing throttling mechanisms in your application to avoid hitting these limits.

Q4: Can I use this server across multiple projects without modifying the codebase?

Yes, the server is built with modularity in mind, allowing you to reuse it across different projects by simply configuring the environment variables accordingly.

Q5: How do I contribute to improving the Raygun MCP Server documentation?

Contributions are always welcome! Feel free to open issues or submit pull requests via GitHub. The community can work together to enhance both the usability and comprehensiveness of the documentation.

👨‍💻 Development & Contribution Guidelines

If you wish to contribute improvements, fixes, or additional features to the Raygun MCP Server, follow these steps:

1. Fork the Repository: Clone the official Raygun MCP Server GitHub repository.
2. Setup Your Environment: Follow the installation instructions located in this README closely.
3. Develop and Test Changes: Use npm scripts for building and testing changes within your development environment.
4. Submit a Pull Request: Once satisfied, create a pull request from your fork to the main repository.

🌐 MCP Ecosystem & Resources

Explore more about the Model Context Protocol and its ecosystem by visiting these resources:

• Model Context Protocol GitHub
• Raygun API Documentation

By integrating the Raygun MCP Server into your development stack, you can significantly boost the efficiency and effectiveness of your AI applications.