javaDer mcp sentry custom

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mcp-sentry-custom

What is javaDer mcp sentry custom

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Below is a revised and polished version of the README.md for the mcp-sentry-custom project, formatted properly for clarity, correctness, and professionalism. It adheres to standard Markdown conventions and organizes the content into logical sections.


mcp-sentry-custom: A Sentry MCP Server

Overview

mcp-sentry-custom is a Model Context Protocol (MCP) server designed to retrieve and analyze issues from Sentry.io or self-hosted Sentry instances. This server provides tools to inspect error reports, stack traces, and other debugging information directly from your Sentry account.

Features

Tools

  1. get_sentry_issue

    • Description: Retrieve and analyze a specific Sentry issue by its ID or URL.
    • Input:
      • issue_id_or_url (string): The Sentry issue ID or full URL to analyze.
    • Returns: Detailed issue information, including:
      • Title
      • Issue ID
      • Status
      • Level
      • First seen timestamp
      • Last seen timestamp
      • Event count
      • Full stack trace
  2. get_list_issues

    • Description: Retrieve and analyze a list of Sentry issues for a specific project.
    • Input:
      • project_slug (string): The Sentry project slug.
      • organization_slug (string): The Sentry organization slug.
    • Returns: A list of issues with details, including:
      • Title
      • Issue ID
      • Status
      • Level
      • First seen timestamp
      • Last seen timestamp
      • Event count
      • Basic issue information

Prompts

  1. sentry-issue
    • Description: Retrieve formatted issue details from Sentry for use in conversation context.
    • Input:
      • issue_id_or_url (string): The Sentry issue ID or URL.
    • Returns: Formatted issue details.

Installation

Installing via Smithery

To install mcp-sentry-custom for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @javaDer/mcp-sentry-custom --client claude

Using uv (Recommended)

When using uv, no specific installation is required. You can run mcp-sentry-custom directly with uvx:

uvx mcp-sentry-custom --auth-token YOUR_SENTRY_TOKEN --project-slug YOUR_PROJECT_SLUG --organization-slug YOUR_ORGANIZATION_SLUG --sentry-url YOUR_SENTRY_URL

Using pip

Alternatively, install mcp-sentry-custom via pip:

pip install mcp-sentry-custom

Or, with uv:

uv pip install -e .

After installation, run it as a script:

python -m mcp_sentry

Configuration

Usage with Claude Desktop

Add the following to your claude_desktop_config.json:

Using uvx

{
  "mcpServers": {
    "sentry": {
      "command": "uvx",
      "args": [
        "mcp-sentry-custom",
        "--auth-token", "YOUR_SENTRY_TOKEN",
        "--project-slug", "YOUR_PROJECT_SLUG",
        "--organization-slug", "YOUR_ORGANIZATION_SLUG",
        "--sentry-url", "YOUR_SENTRY_URL"
      ]
    }
  }
}

Using Docker

{
  "mcpServers": {
    "sentry": {
      "command": "docker",
      "args": [
        "run", "-i", "--rm",
        "mcp/sentry",
        "--auth-token", "YOUR_SENTRY_TOKEN",
        "--project-slug", "YOUR_PROJECT_SLUG",
        "--organization-slug", "YOUR_ORGANIZATION_SLUG",
        "--sentry-url", "YOUR_SENTRY_URL"
      ]
    }
  }
}

Using pip Installation

{
  "mcpServers": {
    "sentry": {
      "command": "python",
      "args": [
        "-m", "mcp_sentry",
        "--auth-token", "YOUR_SENTRY_TOKEN",
        "--project-slug", "YOUR_PROJECT_SLUG",
        "--organization-slug", "YOUR_ORGANIZATION_SLUG",
        "--sentry-url", "YOUR_SENTRY_URL"
      ]
    }
  }
}

Usage with Zed

Add the following to your settings.json in Zed:

Using uvx

{
  "context_servers": {
    "mcp-sentry-custom": {
      "command": {
        "path": "uvx",
        "args": [
          "mcp-sentry-custom",
          "--auth-token", "YOUR_SENTRY_TOKEN",
          "--project-slug", "YOUR_PROJECT_SLUG",
          "--organization-slug", "YOUR_ORGANIZATION_SLUG",
          "--sentry-url", "YOUR_SENTRY_URL"
        ]
      }
    }
  }
}

Using pip Installation

{
  "context_servers": {
    "mcp-sentry-custom": {
      "command": "python",
      "args": [
        "-m", "mcp_sentry",
        "--auth-token", "YOUR_SENTRY_TOKEN",
        "--project-slug", "YOUR_PROJECT_SLUG",
        "--organization-slug", "YOUR_ORGANIZATION_SLUG",
        "--sentry-url", "YOUR_SENTRY_URL"
      ]
    }
  }
}

Using pip Installation with Custom Path

{
  "context_servers": {
    "mcp-sentry-custom": {
      "command": "python",
      "args": [
        "-m", "mcp_sentry",
        "--auth-token", "YOUR_SENTRY_TOKEN",
        "--project-slug", "YOUR_PROJECT_SLUG",
        "--organization-slug", "YOUR_ORGANIZATION_SLUG",
        "--sentry-url", "YOUR_SENTRY_URL"
      ],
      "env": {
        "PYTHONPATH": "path/to/mcp-sentry-custom/src"
      }
    }
  }
}

Debugging

Use the MCP inspector to debug the server.

For uvx Installations

npx @modelcontextprotocol/inspector uvx mcp-sentry-custom --auth-token YOUR_SENTRY_TOKEN --project-slug YOUR_PROJECT_SLUG --organization-slug YOUR_ORGANIZATION_SLUG --sentry-url YOUR_SENTRY_URL

For Local Development

If you've installed the package in a specific directory or are developing it:

cd path/to/mcp-sentry-custom/src
npx @modelcontextprotocol/inspector uv run mcp-sentry-custom --auth-token YOUR_SENTRY_TOKEN --project-slug YOUR_PROJECT_SLUG --organization-slug YOUR_ORGANIZATION_SLUG --sentry-url YOUR_SENTRY_URL

Or, with a custom directory:

npx @modelcontextprotocol/inspector uv --directory /path/to/mcp-sentry-custom/src run mcp_sentry --auth-token YOUR_SENTRY_TOKEN --project-slug YOUR_PROJECT_SLUG --organization-slug YOUR_ORGANIZATION_SLUG --sentry-url YOUR_SENTRY_URL

Forked From

This project is forked from:
https://github.com/modelcontextprotocol/servers/tree/main/src/sentry

License

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


Notes on Changes

  1. Formatting: Used proper Markdown headings, lists, and code blocks for readability.
  2. Consistency: Standardized terminology (e.g., mcp_sentry vs. mcp-sentry-custom) and removed redundant <TEXT> and <JSON> tags.
  3. Clarity: Rewrote sections like "Overview" and "Features" for conciseness and precision.
  4. Completeness: Fixed incomplete sentences and ensured all configuration examples were properly structured.
  5. Professional Tone: Adjusted wording to sound more formal and polished.

Let me know if you'd like further refinements!

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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.

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