Raygun MCP Server Integration

What does “Raygun” MCP Server do?

The Raygun MCP Server is a bridge between AI assistants and Raygun’s API V3 endpoints, enabling seamless interaction with Crash Reporting and Real User Monitoring applications. By exposing Raygun’s API features through the Model Context Protocol (MCP), this server allows AI-powered workflows to automate and streamline tasks such as error management, deployment tracking, performance monitoring, source map handling, and team management. Developers can use this MCP server to trigger actions, query data, and manage their Raygun applications programmatically, enhancing productivity and accelerating troubleshooting and release cycles.

List of Prompts

No explicit prompt templates are documented in the repository.

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List of Resources

No explicit resources are documented in the repository.

Applications

• list_applications – List all applications under your account.
• get_application – Get details of an application by identifier.
• get_application_by_api_key – Retrieve application details using the API key.
• regenerate_application_api_key – Generate a new API key for an application.

Error Management

• list_error_groups – List error groups for an application.
• get_error_group – Get detailed information about a specific error group.
• resolve_error_group – Mark an error group as resolved.
• activate_error_group – Mark an error group as active.
• ignore_error_group – Mark an error group as ignored.
• permanently_ignore_error_group – Permanently ignore an error group.

Deployment Management

• list_deployments – List deployments for an application.
• get_deployment – Get deployment details by identifier.
• delete_deployment – Remove a deployment.
• update_deployment – Update deployment information.
• reprocess_deployment_commits – Reprocess deployment commit data.

User & Session Management

• list_customers – List customers for an application.
• list_sessions – List user sessions for an application.
• get_session – Retrieve detailed session information.

Performance Monitoring

• list_pages – List monitored pages for an application.
• get_page_metrics_time_series – Retrieve time-series performance metrics.
• get_page_metrics_histogram – Get a histogram of performance metrics.
• get_error_metrics_time_series – Get time-series error metrics.

Source Maps

• list_source_maps – List source maps for an application.
• get_source_map – Retrieve source map details.
• update_source_map – Update source map information.
• delete_source_map – Remove a source map.
• upload_source_map – Upload a new source map.
• delete_all_source_maps – Remove all source maps.

Team Management

• list_invitations – List pending team invitations.
• send_invitation – Send a new team invitation.
• get_invitation – Get invitation details.
• revoke_invitation – Revoke a pending invitation.

Use Cases of this MCP Server

• Error Management Automation
  Enable AI agents to list, resolve, ignore, or activate error groups automatically, streamlining the triage and management of application errors.
• Deployment Tracking and Management
  Programmatically list, update, or delete deployments and reprocess commit data, allowing teams to track release health and automate deployment workflows.
• Performance Monitoring
  Access real user monitoring data, retrieve metrics, and analyze performance trends or bottlenecks directly via AI workflows.
• Source Map Management
  Automate the upload, update, or removal of source maps, ensuring debugging and error tracking remain accurate without manual intervention.
• Team and Session Management
  Manage team invitations, sessions, and customer lists, facilitating team onboarding/offboarding and monitoring user sessions for security or analytics purposes.

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How to set it up

Windsurf

No specific setup instructions for Windsurf are provided in the repository.

Claude

1. Ensure Node.js and npm are installed on your system.
2. Obtain your Raygun PAT token.
3. Locate your claude_desktop_config.json file (~/Library/Application Support/Claude/claude_desktop_config.json on MacOS or %APPDATA%/Claude/claude_desktop_config.json on Windows).
4. Add the Raygun MCP Server configuration:

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

5. Save the file and restart Claude Desktop.

Securing API Keys:
Store your PAT token as an environment variable in the config as shown above.

Cursor

No specific setup instructions for Cursor are provided in the repository.

Cline

No specific setup instructions for Cline are provided in the repository.

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "raygun": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “raygun” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Our opinion

The Raygun MCP Server provides comprehensive tooling for managing Raygun applications via MCP, with clear documentation of tools and setup for Claude. However, it lacks prompt templates, explicit resource definitions, and instructions for some platforms. Sampling and Roots support are not mentioned. Overall, good for tool coverage and security setup, but missing some advanced MCP features.

MCP Score

MCP Table Score: 6/10 – Solid tool support and security, but missing prompt templates, resources, advanced MCP features, and multi-platform setup details.