Sentry Integration MCP Servers

Sentry MCP servers provide interfaces for LLMs to interact with Sentry's error monitoring and performance tracking platform. These servers enable AI models to analyze errors, track performance issues, and assist in debugging applications.

{
  "mcpServers": {
    "sentry": {
      "command": "uvx",
      "args": ["mcp-server-sentry", "--auth-token", "YOUR_SENTRY_TOKEN"]
    }
  }
}

Overview

The MCP Sentry Server enables AI models to interact directly with Sentry's error monitoring and performance tracking platform through the Model Context Protocol (MCP). It provides a standardized interface for error analysis, performance monitoring, and automated issue management while maintaining security and data privacy. 1

Key features include:

  • Error tracking and analysis
  • Performance monitoring
  • Issue management and resolution
  • Alert configuration
  • Stack trace analysis
  • Release tracking
  • Environment management
  • Real-time monitoring

Tools

Sources

Footnotes

  1. https://github.com/modelcontextprotocol/servers/tree/main/src/sentry ↩

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