"Viewing SonarQube Code Analysis Findings for My Code" matching MCP servers:

Provides comprehensive code analysis through three MCP servers: static analysis for code quality and security, dependency analysis for package management and vulnerabilities, and complexity analysis for maintainability assessment across multiple programming languages.

Enables multi-project code analysis by invoking project-provided Claude Code agents and skills, with optional SVN updates, returning Markdown reports to MCP clients.

Turns AI assistants into full-stack software engineers with 36 tools for cognitive reasoning, code validation, project scaffolding, and AI/IDE configuration generation across 130+ programming languages, databases, and frameworks.

A Model Context Protocol server that helps large language models process code repositories by providing file tree generation, code merging, and code analysis capabilities.

Allows agents to lookup code snippets in your project. Uses a remote MCP server with a collection of code snippets, with support for automatic project language detection.

Enables AI assistants to surgically extract and analyze code, reducing token usage and costs by up to 200x compared to reading entire files.

Enables Claude AI to run terminal commands, perform file operations, and manage git in a project directory via the Model Context Protocol.

An MCP server to create secure code sandbox environment for executing code within Docker containers.

MCP server for automated code review using AI agents. It analyzes code diffs or file paths for bugs, security issues, and style violations.

A self-hosted MCP and HTTP server for TypeScript code intelligence, providing AI agents with fast semantic code navigation tools like finding definitions, references, implementations, file outlines, dependency graphs, and search.

Local-first code indexer that provides deep code understanding for Claude and other LLMs with symbol/text search across 48+ languages, semantic search capabilities, and real-time index updates through the Model Context Protocol.

Builds rich code graphs from TypeScript/NestJS codebases using AST analysis and Neo4j, enabling semantic search, natural language querying, and intelligent graph traversal to provide deep contextual understanding of code relationships and dependencies.

Open-source AI code review MCP server for local git diff auditing with deterministic security rules and AI-powered analysis using any OpenAI-compatible model.

Multi-provider embedding MCP server with local Milvus for semantic code search. Works with Claude Code, Cursor, Windsurf, and other MCP-compatible IDEs.

Allows LLM tools like Claude Desktop and Cursor AI to access and summarize code files through a Model Context Protocol server, providing structured access to codebase content without manual copying.

An MCP server that lets Claude Code delegate coding tasks such as code generation, review, refactoring, and test writing to a local Ollama instance running a Qwen3 model.

Indexes a mono-repo into a knowledge graph and provides MCP tools to query code structure—packages, components, routes, HTTP calls—without file reads or grep round-trips.

An MCP server that scans codebases to extract structural information (classes, functions, etc.) with flexible filtering options and outputs in LLM-friendly formats.

Enables AI assistants to review GitHub and GitLab pull requests and merge requests, supporting multiple transports and custom review rules.

A security filter that blocks dangerous code patterns by comparing normalized structural syntax trees against a blacklist of known threats using vector embeddings. It acts as a gatekeeper to prevent malicious code execution by identifying dangerous structures regardless of specific identifiers or literals.