Raygun MCP Server – Error Monitoring for AI Agents
Raygun's remote MCP server gives AI coding assistants authenticated access to live crash reporting, deployment, customer-session, and real user monitoring context. Agents can investigate application errors, correlate failures with deployments, analyze performance trends, and help teams act on Raygun observability data from supported MCP clients.
Overview
Raygun MCP Server is a remote Model Context Protocol server for Raygun's application monitoring platform. It connects AI coding assistants to Raygun crash reporting and real user monitoring data so they can investigate production issues with current application context rather than relying only on pasted logs or static model knowledge. Raygun documents the hosted endpoint as https://api.raygun.com/v3/mcp and positions it as a remote-first server with built-in authentication and no local server process to maintain.
What the MCP server enables
The server exposes Raygun-focused tools for application observability workflows. Documented tool categories include application discovery, error management, deployment tracking, customer and session investigation, performance metrics, and team invitation management. An AI assistant can list and search applications, inspect error groups, browse individual error instances, retrieve stack trace and context, update error group status, add comments, list deployments, create deployment records, analyze error trends, inspect page performance, and review user sessions.
These capabilities are useful when an agent needs live monitoring data to explain a production bug, compare an error spike with recent releases, identify affected customers, or summarize performance changes across monitored pages.
When to use it
Use Raygun MCP Server when an engineering agent needs to triage application errors or real user monitoring signals stored in Raygun. Practical prompts include asking for the most recent error groups, investigating whether a deployment introduced new crashes, reviewing a customer's recent sessions, or analyzing performance trends over the last several days. It is especially relevant inside coding assistants that can combine Raygun context with repository context to propose or validate fixes.
Connection and authentication
Raygun documents the MCP server as a hosted remote endpoint using HTTP. Clients connect to https://api.raygun.com/v3/mcp and pass a Raygun Personal Access Token using the Authorization: Bearer ... header. The token must be created in Raygun, granted appropriate permissions for the workflow, and kept out of source control. Some clients can connect directly to the remote URL, while others may use mcp-remote as a local bridge to the same endpoint.
Key considerations
Access is limited by the Raygun account, subscription, token permissions, and the applications available to that token. Several tools can change Raygun state, such as updating error status, adding comments, creating or deleting deployment records, regenerating application API keys, and managing invitations, so teams should grant least-privilege PAT scopes and review agent actions before allowing changes in production workflows. Because the server is remote-first, users do not need to install or update a local Raygun MCP package, but network access to Raygun's API endpoint is required.
Supported Transports
streamable_http
URL: https://api.raygun.com/v3/mcp
Frequently Asked Questions
- When should an AI agent use the Raygun MCP server?
- Use it when an AI assistant needs live Raygun observability context to investigate production errors, review crash groups, correlate issues with deployments, inspect affected customers or sessions, and analyze real user monitoring performance trends.
- What does this MCP server add to an AI agent's capabilities?
- It gives the agent access to Raygun application, crash reporting, deployment, customer-session, and performance data through documented MCP tools, allowing the agent to reason over current monitoring data instead of only static context or copied stack traces.
- What can the AI agent access or manage through this server?
- Documented tools cover listing and searching applications, investigating error groups and instances, updating error group status, adding comments, listing and managing deployments, searching customers, listing sessions, analyzing performance metrics, and managing team invitations.
- How is authentication configured for this MCP server?
- Raygun requires a Personal Access Token. MCP clients pass it to the hosted endpoint in the `Authorization` header as `Bearer ${RAYGUN_PAT}`. The token should have only the permissions needed for the intended workflow and must not be committed to source control.
- Which transport should be used for this MCP server?
- Use the hosted Streamable HTTP endpoint at `https://api.raygun.com/v3/mcp`. Raygun documents this as the remote MCP connection method; local bridge commands such as `mcp-remote` are client-specific wrappers around the same remote endpoint, not a separate Raygun-hosted transport.