mcp-sentry: A Sentry MCP server

@MCP-100

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Basic information

About mcp-sentry: A Sentry MCP server

A Model Context Protocol server for retrieving and analyzing issues from Sentry.io

#python #sentry #mcp #mcp-server

mcp-sentry: A Sentry MCP server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "mcp-sentry": {
      "command": "npx",
      "args": [
        "-y",
        "@smithery/cli",
        "install",
        "@qianniuspace/mcp-sentry",
        "--client",
        "claude"
      ]
    }
  }
}

mcp-sentry: A Sentry MCP server tools

`issue_id_or_url` (string): Sentry issue ID or URL to analyze

Issue details including:

`project_slug` (string): Sentry project slug to analyze

List of issues with details including:

Overview

What is mcp-sentry?

mcp-sentry is a Model Context Protocol server for retrieving and analyzing issues from Sentry.io. It provides tools to inspect error reports, stacktraces, and other debugging information from your Sentry account, aimed at developers using Sentry for error monitoring.

How to use mcp-sentry?

Install via Smithery, uv (uvx), or pip. Configure with your Sentry auth token, project slug, and organization slug in your MCP client (e.g., Claude Desktop or Zed). Invoke the server using the commands specified in the configuration, and use the tools get_sentry_issue and get_list_issues or the prompt sentry-issue to retrieve Sentry issue data.

Key features of mcp-sentry

Retrieve a Sentry issue by ID or URL.
List Sentry issues by project and organization slug.
Return issue details: title, status, level, timestamps, event count.
Provide full stacktrace for an issue.
Includes a prompt for conversational issue retrieval.

Use cases of mcp-sentry

Debugging a specific error by fetching its full stacktrace.
Monitoring recent issues in a project for trend analysis.
Integrating Sentry error data into AI‑assisted debugging workflows.

Frequently asked questions

What are the runtime requirements?

The server requires Python and can be run via `uvx` or pip. A Sentry authentication token, project slug, and organization slug are needed for configuration.

Where does my Sentry data live?

Data is retrieved from your Sentry.io account; the server acts as a bridge and does not store data locally.

What transport does mcp-sentry use?

The server uses the standard MCP stdio transport, invoked via command-line arguments.

How do I authenticate with Sentry?

Authentication is done by passing your Sentry auth token as a command-line argument (`--auth-token`).

Are there any known limitations?

The README does not mention any specific limitations.

Comments

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