Sentry

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by modelcontextprotocol

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Retrieving and analyzing issues from Sentry.io

What is Sentry

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:

"mcpServers": {
  "sentry": {
    "command": "uvx",
    "args": ["mcp-server-sentry", "--auth-token", "YOUR_SENTRY_TOKEN"]
  }
}
"mcpServers": {
  "sentry": {
    "command": "docker",
    "args": ["run", "-i", "--rm", "mcp/sentry", "--auth-token", "YOUR_SENTRY_TOKEN"]
  }
}
"mcpServers": {
  "sentry": {
    "command": "python",
    "args": ["-m", "mcp_server_sentry", "--auth-token", "YOUR_SENTRY_TOKEN"]
  }
}

Usage with Zed

Add to your Zed settings.json:

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

What is MCP?

MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications, providing a standardized way to connect AI models to different data sources and tools.

What are MCP Servers?

MCP Servers are lightweight programs that expose specific capabilities through the standardized Model Context Protocol. They act as bridges between LLMs like Claude and various data sources or services, allowing secure access to files, databases, APIs, and other resources.

How do MCP Servers work?

MCP Servers follow a client-server architecture where a host application (like Claude Desktop) connects to multiple servers. Each server provides specific functionality through standardized endpoints and protocols, enabling Claude to access data and perform actions through the standardized protocol.

Are MCP Servers secure?

Yes, MCP Servers are designed with security in mind. They run locally with explicit configuration and permissions, require user approval for actions, and include built-in security features to prevent unauthorized access and ensure data privacy.