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Sentry: Instant Error Tracking & Smart Analysis - MCP Implementation

Sentry: Instant Error Tracking & Smart Analysis

Sentry: Crush bugs before they crush your users. Instant error tracking & smart analysis from Sentry.io turns chaos into clarity—so you fix what matters, fast. Game-changers code here.

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About Sentry

What is Sentry: Instant Error Tracking & Smart Analysis?

Sentry: Instant Error Tracking & Smart Analysis is a dedicated Model Context Protocol (MCP) server designed to streamline the process of retrieving and interpreting error data from Sentry.io. This tool empowers developers to access critical debugging information—including stack traces, error statuses, and event timelines—directly within their workflow, eliminating the need for manual context switching between platforms.

How to Use Sentry: Instant Error Tracking & Smart Analysis?

Installation Methods

Quickly set up the server using either uvx (recommended) for simplified dependency management:

uvx mcp-server-sentry --auth-token YOUR_SENTRY_TOKEN

Or via pip for traditional package installation:

pip install mcp-server-sentry
python -m mcp_server_sentry --auth-token YOUR_SENTRY_TOKEN

Integration Setup

Configure the server in your environment:

  • For Claude Desktop, add the server definition to claude_desktop_config.json:
    • "mcpServers": {
  "sentry": {
    "command": "uvx",
    "args": ["mcp-server-sentry", "--auth-token", "YOUR_SENTRY_TOKEN"]
  }
}
  • For Zed, update settings.json with the server command details.

Sentry Features

Key Features of Sentry: Instant Error Tracking & Smart Analysis

  • Granular Issue Inspection: Retrieve full stack traces, error metadata, and timestamped event histories via the get_sentry_issue tool.
  • Contextual Analysis: The sentry-issue prompt formats raw data into actionable insights for AI-driven debugging sessions.
  • Seamless Authentication: Securely pass Sentry API tokens through command-line arguments for frictionless integration.
  • Cross-Platform Support: Works natively with tools like Claude Desktop and Zed for unified workflow integration.

Use Cases for Sentry: Instant Error Tracking & Smart Analysis

  • Real-Time Debugging: Rapidly analyze production errors without leaving your IDE or chat interface.
  • Automated Error Profiling: Leverage AI to correlate error data with code changes or user interactions.
  • Team Collaboration: Share contextual error insights across development teams through integrated platforms.

Sentry FAQ

Frequently Asked Questions

Do I need programming knowledge to use this server?

Basic command-line familiarity is required for setup, but the server abstracts complex Sentry API interactions into user-friendly workflows.

Which platforms are supported?

Officially tested with Claude Desktop and Zed, but compatible with any MCP-compliant environment.

Is the server open-source?

Yes, the implementation adheres to open standards, and contributions are welcome through the official GitHub repository.

Content

mcp-server-sentry: A Sentry MCP server

Overview

A Model Context Protocol server for retrieving and analyzing issues from Sentry.io. This server provides tools to inspect error reports, stacktraces, and other debugging information from your Sentry account.

Tools

  1. get_sentry_issue
    * Retrieve and analyze a Sentry issue by ID or URL
    * Input:
    • issue_id_or_url (string): Sentry issue ID or URL to analyze
      • Returns: Issue details including:
    • Title
    • Issue ID
    • Status
    • Level
    • First seen timestamp
    • Last seen timestamp
    • Event count
    • Full stacktrace

Prompts

  1. sentry-issue
    * Retrieve issue details from Sentry
    * Input:
    • issue_id_or_url (string): Sentry issue ID or URL
      • Returns: Formatted issue details as conversation context

Installation

Using uv (recommended)

When using uv no specific installation is needed. We will use uvx to directly run mcp-server-sentry.

Using PIP

Alternatively you can install mcp-server-sentry via pip:

pip install mcp-server-sentry

After installation, you can run it as a script using:

python -m mcp_server_sentry

Configuration

Usage with Claude Desktop

Add this to your claude_desktop_config.json:

Using uvx

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

Using pip installation

json "mcpServers": { "sentry": { "command": "python", "args": ["-m", "mcp_server_sentry", "--auth-token", "YOUR_SENTRY_TOKEN"] } }

Usage with Zed

Add to your Zed settings.json:

Using uvx

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

Using pip installation

json "context_servers": { "mcp-server-sentry": { "command": "python", "args": ["-m", "mcp_server_sentry", "--auth-token", "YOUR_SENTRY_TOKEN"] } },

Debugging

You can use the MCP inspector to debug the server. For uvx installations:

npx @modelcontextprotocol/inspector uvx mcp-server-sentry --auth-token YOUR_SENTRY_TOKEN

Or if you've installed the package in a specific directory or are developing on it:

cd path/to/servers/src/sentry npx @modelcontextprotocol/inspector uv run mcp-server-sentry --auth-token YOUR_SENTRY_TOKEN

License

This MCP server is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.

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