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sapientpants/sonarqube-mcp-server

by Various

Model Context Protocol (MCP) server for SonarQube

S

MCP

sapientpants/sonarqube-mcp-server

Added 1 June 2026

#mcp #mcp-server #model-context-protocol #model-context-protocol-servers #sonarcloud #sonarqube #typescript

Overview

A Model Context Protocol (MCP) server that exposes SonarQube code quality and security analysis data to AI assistants. It allows tools like Claude to query SonarQube projects, issues, and metrics through the MCP standard interface.

Best for

Best for
Developers using AI coding assistants who need to incorporate SonarQube code quality data into their workflow

Use cases

  • Retrieve code quality issues from SonarQube during AI-assisted code review
  • Query SonarQube project metrics and security hotspots via natural language
  • Integrate SonarQube analysis results into AI-driven development workflows

Notes

A Model Context Protocol (MCP) server that exposes SonarQube code quality and security analysis data to AI assistants. It allows tools like Claude to query SonarQube projects, issues, and metrics through the MCP standard interface.

99 stars on GitHub. Last updated 2025-11-14.

Use cases

  • Retrieve code quality issues from SonarQube during AI-assisted code review
  • Query SonarQube project metrics and security hotspots via natural language
  • Integrate SonarQube analysis results into AI-driven development workflows

Pros

  • Open source with 99 stars, indicating community interest and transparency
  • Follows the MCP standard, enabling interoperability with multiple AI assistants
  • Simplifies access to SonarQube data without custom API integrations

Cons

  • Requires a running SonarQube instance, adding infrastructure overhead
  • MCP adoption is still limited, so compatibility is restricted to supporting AI tools
  • Feature set depends on SonarQube’s API; may not cover all analysis capabilities

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Open source with 99 stars, indicating community interest and transparency
  • Follows the MCP standard, enabling interoperability with multiple AI assistants
  • Simplifies access to SonarQube data without custom API integrations

Cons

  • Requires a running SonarQube instance, adding infrastructure overhead
  • MCP adoption is still limited, so compatibility is restricted to supporting AI tools
  • Feature set depends on SonarQube's API; may not cover all analysis capabilities
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