FastMCP SonarQube Metrics MCP Server

@ArchAI-Labs

代码仓库

基本信息

分类

开发工具

许可证

Apache-2.0

传输方式

stdio

作者

ArchAI-Labs

关于 FastMCP SonarQube Metrics MCP Server

Chat with your SonarQube data: explore metrics, compare trends, and track issues—effortlessly.

#sonarqube #mcp-server

FastMCP SonarQube Metrics MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "fastmcp-sonarqube-metrics": {
      "command": "uv",
      "args": [
        "run",
        "mcp",
        "dev",
        "<server_name>"
      ]
    }
  }
}

FastMCP SonarQube Metrics MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is FastMCP SonarQube Metrics?

It is a set of tools built with the FastMCP framework that retrieve metrics, historical data, component tree details, and issues from SonarQube projects. Designed for developers, DevOps engineers, and analysts who need programmatic access to SonarQube data for reporting, analysis, and integration.

How to use FastMCP SonarQube Metrics?

Clone the repository, set environment variables (SONARQUBE_URL, SONARQUBE_TOKEN, TRANSPORT) in a .env file, install Python dependencies, then run server.py. Launch the included test client with client_test.py or integrate with Claude Desktop by configuring its MCP server settings. A hosted deployment is also available on Fronteir AI.

Key features of FastMCP SonarQube Metrics

Health check: get_status verifies the SonarQube instance.
Project management: create and delete SonarQube projects.
List all accessible SonarQube projects, optionally filtered.
Retrieve current metrics: bugs, vulnerabilities, code smells, coverage, duplication.
Fetch historical metrics with optional date filters.
Get component tree metrics with automatic pagination.
Retrieve project issues filtered by type, severity, and resolution.

Use cases of FastMCP SonarQube Metrics

Automate SonarQube metric collection for dashboards or reports.
Integrate code quality data into CI/CD pipelines.
Build custom analytics tools that consume SonarQube data.
Perform health checks and monitor project status programmatically.
Extract issue lists for triage or compliance tracking.

常见问题

What are the prerequisites to use this server?

Python 3.7+, a running SonarQube instance with API access, a valid SonarQube API token, and installed packages: fastmcp, httpx, pydantic, python-dotenv.

What transport modes are supported?

The server supports both `stdio` and `sse` (Server-Sent Events) transport, configured via the `TRANSPORT` environment variable.

How do I configure this server with Claude Desktop?

Add a JSON entry to `claude_desktop_config.json` specifying the command `uv` with the directory pointing to the cloned repository and running `server.py`.

Is there a hosted version available?

Yes, a hosted deployment is available on Fronteir AI at the URL provided in the README.

Are there any known limitations?

The project is a work in progress; some features may not be perfect.

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