Is Sentry MCP easy to set up and integrate?

Yes, it offers straightforward installation via `cargo install` or `mise` and requires minimal configuration with your Sentry API token and host. Integration with MCP clients is simple via a JSON configuration.

How does Sentry MCP enhance my development workflow?

It provides contextual Sentry insights—like issues and traces—directly in your development environment, streamlining debugging, understanding performance bottlenecks, and improving overall efficiency without switching tools.

What Sentry information can I retrieve using this tool?

You can access detailed Sentry issue information (metadata, tags, stacktraces), comprehensive distributed trace data (span tree, timing), and search issue events using Sentry's query syntax.

Sentry MCP integrates Sentry's API with the Model Context Protocol, enabling developers to access Sentry issue and trace details directly within their MCP-compatible development environments.

Sentry

Name: Sentry
Author: utapyngo

byutapyngo

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Desarrollo de API

Herramientas para Desarrolladores

Analíticas y Monitorización

Integrates Sentry's API into the Model Context Protocol (MCP) to provide issue and trace details for contextual development workflows.

Acerca de

Sentry is a fast and minimal Model Context Protocol (MCP) server implemented in Rust, designed to seamlessly interact with Sentry's API. It empowers developers to access critical Sentry data directly from their MCP client, enabling efficient debugging and monitoring. With capabilities to retrieve detailed issue information, analyze distributed traces, and search issue events, Sentry streamlines the process of integrating Sentry's robust error tracking and performance monitoring into an intelligent, context-aware development environment.

Características Principales

Access distributed trace details with span tree and timing information
Minimalist design for efficient performance
2 GitHub stars
Easy integration with MCP clients via simple configuration
Retrieve detailed Sentry issue information including metadata, tags, and stacktraces
Search Sentry issue events using Sentry's query syntax

Casos de Uso

Analyzing distributed traces to debug performance problems directly from development tools
Contextually fetching Sentry issue details within an MCP-enabled editor or terminal
Integrating Sentry data into automated developer workflows
Programmatically searching for specific events within a Sentry issue for faster triage

Acerca de

Características Principales

Access distributed trace details with span tree and timing information
Minimalist design for efficient performance
2 GitHub stars
Easy integration with MCP clients via simple configuration
Retrieve detailed Sentry issue information including metadata, tags, and stacktraces
Search Sentry issue events using Sentry's query syntax

Casos de Uso

Analyzing distributed traces to debug performance problems directly from development tools
Contextually fetching Sentry issue details within an MCP-enabled editor or terminal
Integrating Sentry data into automated developer workflows
Programmatically searching for specific events within a Sentry issue for faster triage