"How to fix SonarQube findings" matching MCP servers:

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.

A server that provides tools for retrieving SonarQube project metrics and quality data through a simplified message-based approach, allowing users to programmatically access metrics, historical data, and component-level information from SonarQube.

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

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.

Enables scanning Python repos for dead code and automatically drafting a branch + PR for the safe subset (unused single-name imports) after running the repo's full test suite. All other findings are reported without modification, and a human always merges.

Enables coding agents to retrieve pull request review findings, reproduce and fix them locally, reply on review threads, report reproduction results, and request fresh reviews.

Security checks for apps built with AI: Trivy and Opengrep findings explained in plain English, with a fix request for your coding agent. Hosted scan by default (only files Git would commit, never secret files) or fully local.

Enables AI agents to repair OCR-mangled Japanese dates only when calendar validation confirms the corrected result, and to check individual dates against their era ranges.

Enables managing audit findings in a SQLite database via natural language, allowing queries and updates without writing SQL.

Text-to-speech MCP server that enables AI assistants to read text aloud on the user's computer using Windows SAPI, with no API key or cloud service required.

MCP server for parsing, validating, building and explaining FIX protocol trading messages — offline, no API keys.

An MCP server that sends plain-text Gmail messages only to a predefined allowlist, using generated recipient IDs instead of email addresses to enforce security.

An autonomous MCP server that uses the Claude Code CLI to solve coding problems without permission prompts.

Enables AI agents to securely connect to and manage remote servers via SSH, with tools for running commands, file operations, log inspection, service management, and system monitoring under configurable access controls and audit logging.

Monitor failing GitHub Actions workflows, auto-fix them with OpenCode, and retry the run — driven by a workflow_run webhook, coordinated through an MCP server.

Enables conversion of YouTube videos to MP3 format through the Youtube To Mp315 API. Supports checking conversion status, retrieving video titles, and asynchronous video-to-audio conversion with customizable quality and time range settings.

Searches Reddit for answers to questions and saves Q&A sessions to Notion.

Connects AI clients to Tenable OT Security, exposing OT/ICS asset inventory, vulnerabilities, events, policies, and findings as read tools, with an opt-in dry-run write layer for asset edits and policy management.

Read-only security audit for Supabase. Surfaces RLS gaps, permissive policies, exposed functions and grants, and returns scored findings with fix SQL that is never executed.

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

Enables AI assistants to automatically recover SonarQube technical debt by fetching issues, running proposal-only worker batches, and integrating verified fixes serially with progress tracking.

Live aircraft and ship positions for an agent, by circle or polygon, with the feeds that reported each contact and how old each fix is. Runs against your own self-hosted Velocity instance, no API keys.

Enables users to convert text into high-quality audio by accessing the OpenAI Text-to-Speech API. It supports customizable model selection and voice options for synthesized speech generation via the MCP protocol.

Enables agents to transform tabular Markdown content into structured, type-inferred records with normalized formatting through an MCP-compatible interface.

A Model Context Protocol (MCP) server for integrating with StackHawk's security scanning platform. Helps developers set up StackHawk, run security scans, and triage findings to fix vulnerabilities — all from within an LLM-powered IDE or chat.

Validates .mcp.json and claude_desktop_config files to catch duplicate server names, missing binaries, invalid environment variables, and unreachable endpoints. Reports each problem along with how to fix it, so silently failing MCP servers can be diagnosed and repaired.

Enables LLMs to query documents using semantic search, supporting PDFs, Word, Excel, and more. Organizes documents by topics from folder structure and provides advanced search features like phrase matching and date filtering.

Enables AI agents to audit KiCad PCB designs through deterministic DRC/ERC checks, spatial heuristics, and multimodal vision review, returning structured, prioritized findings with coordinates and fix guidance.

Exposes the code-and-dependency graph over MCP so clients can list and explain CVE findings from public endpoints, find supply-chain hubs, recommend and plan upgrades, verify a fix in a rebuilt scratch graph, and propose a draft fix PR. Queries are read-only and no tool executes an action.

Deterministic Markdown-to-Word (.docx) publishing compiler with native OMML equations, three-line tables, CSL citations, and quality gates for AI agents.