"How to fix SonarQube findings" matching MCP servers:

An MCP server for SonarQube that enables LLM agents to discover projects, analyze code quality metrics, check Quality Gate status, search issues with filters, and rank projects by worst-performing metrics. It provides read-only, safe access to SonarQube instances with structured outputs and error handling.

Read-only MCP server for self-hosted SonarQube Community Build 26.4+: lets AI agents (Claude Code, Cursor, Copilot) read issues, security hotspots, rules and code snippets to fix findings locally

Enables Cursor AI to query SonarQube for pull request metrics, issues, file issues, and duplication reports directly, without manual data export.

A read-only MCP server that provides AI assistants with structured access to SonarQube projects, issues, metrics, and rules. It enables safe analysis of code quality and security findings through a set of validated, safety-first tools.

MCP server that exposes code review tasks from the Fix My Comments VS Code extension to AI agents, enabling them to list, retrieve, reply to, and update task statuses.

Enables read-only exploration of SonarQube projects, explaining why a quality gate is red and searching unresolved issues, reading metrics and source snippets around a finding. All six tools are idempotent and leave the SonarQube instance untouched.

A Model Context Protocol (MCP) server that provides AI assistants with access to SonarQube code quality, security, and project analytics data.

Read-only MCP server that exposes SonarQube Web API tools for issue retrieval, quality gate status, and source context, enabling coding agents to fix code issues.

A Python MCP server for SonarQube, enabling AI agents to query projects, issues, quality gates, coverage, and security hotspots.

Multi-client MCP server for integrating SonarQube 10.6+ code quality analysis with Amazon Q Developer, supporting multiple simultaneous users, branch analysis, and issue management.

Server for SonarQube Give AI assistants direct access to your code quality, security & analysis data

Enables VS Code's AI assistant to query and manage SonarQube projects, quality gates, measures, issues, hotspots, branches, and system status through the SonarQube REST API over stdio.

Enables seamless integration with SonarQube Server or Cloud for code quality and security analysis. Supports querying project metrics, issues, and analyzing code snippets directly within the agent context.

A lightweight MCP for SonarQube reports

Enables access to SonarQube code quality analysis through MCP, including issue searching, metrics retrieval, and quality gate status.

MCP server that exposes SonarQube data as AI agent tools, enabling project discovery, quality gates, measures, issues, hotspots, rule explanations, source code, and raw API access.

Enables MCP clients to run Python static analysis and receive evidence-backed findings with causation traces, reproducible witnesses, and suggested verified patches.

Scans code strings for hardcoded secrets (AWS keys, tokens, private keys, etc.) and returns redacted findings, helping AI coding agents catch secrets before writing or committing code.

Scans diffs, files, and snippets for leaked secrets like AWS keys, GitHub tokens, and private keys, returning redacted findings while running fully locally without network calls.

Enables static security audit of Solidity smart contracts by analyzing source code or deployed bytecode for vulnerabilities, providing risk scores and detailed findings.

Enables AI coding tools to run CheckMyLaunch scans on GitHub repos or live URLs and retrieve findings and repair prompts directly within the chat.

A Model Context Protocol (MCP) server for interacting with SonarQube code quality platform.

MCP server that reviews and fixes code across four dimensions (security, standards, production readiness, sustainability), runs tests to verify fixes, and provides findings with diffs.

Enables coding agents to compile supplied files, run optional focused tests, and get static findings across ten programming languages, providing a deterministic feedback loop on the code they are about to return.

MCP server that provides a 216-rule, framework-aware Kotlin/JVM security analyzer, enabling AI coding agents to query real security findings while writing code.

Enables AI assistants to scan Terraform and Dockerfiles for security misconfigurations, returning structured Checkov findings that can be explained in plain language.

Enables local SOC 2 compliance work by scanning Infrastructure-as-Code, mapping findings to SOC 2 Trust Services Criteria, explaining risks in plain English, and drafting audit-ready documents without uploading files.

Enables independent, read-only adversarial review of candidate test cases and bug findings, returning a review delta that authoring agents reconcile before writing final artifacts.

Enables scanning diffs or code blobs for leaked secrets, returning a verdict with severity and masked findings, all processed locally with no data sent externally.

Agent-native "safe to ship?" security gate for AI-generated code. Uses real parsers and inter-rocedural taint analysis (JS/TS, Python, Go) to flag the classes AI coding agents get wrong — secrets, SQL injection, SS, SSRF, path traversal, command injection, weak JWT/CORS — and ranks findings by confidence. Exposes a scan tool over MCP.