MCPs tagged with # Code Analysis

godoc-mcp is a Model Context Protocol (MCP) server that provides efficient, structured access to Go package documentation for large language models. It enables LLMs to understand Go projects without reading entire source files by supplying essential documentation and source code at varying levels of granularity. The tool supports project navigation, automatic module setup, caching, and works offline for both standard and third-party Go packages.

• ⭐ 88
• MCP
• mrjoshuak/godoc-mcp

GitHub MCP Server enables AI tools such as agents, assistants, and chatbots to interact natively with the GitHub platform. It allows these tools to access repositories, analyze code, manage issues and pull requests, and automate workflows using the Model Context Protocol (MCP). The server supports integration with multiple hosts, including VS Code and other popular IDEs, and can operate both remotely and locally. Built for developers seeking to enhance AI-powered development workflows through seamless GitHub context access.

• ⭐ 24,418
• MCP
• github/github-mcp-server

Bugsy provides a command-line interface for automatic remediation of security vulnerabilities in codebases. It integrates with popular SAST tools such as Checkmarx, Snyk, CodeQL, and Fortify to identify issues and generate fixes. Bugsy supports both direct scanning and analysis of pre-generated SAST reports, and also operates as a Model Context Protocol (MCP) server for AI assistant integrations. The tool enables developers to streamline the vulnerability fixing process and improve code security efficiently.

• ⭐ 60
• MCP
• mobb-dev/bugsy

Gitingest-MCP serves as a Model Context Protocol (MCP) server compatible with context-aware AI tools. It enables MCP clients such as Claude Desktop, Cline, Cursor, and others to quickly and efficiently extract key information from GitHub repositories, including summaries, the directory tree, and individual file contents. It supports installation via Smithery or manual configuration and is designed for seamless integration into the MCP client ecosystem. Documentation provides guidance on installation, configuration, and debugging.

• ⭐ 131
• MCP
• puravparab/Gitingest-MCP

Implements a server utilizing the Model Context Protocol to enable Claude Code functionality, allowing AI agents to perform advanced codebase analysis, modification, and command execution. Supports code understanding, file management, and integration with various LLM providers. Offers specialized tools for searching, editing, and delegating tasks, with robust support for Jupyter notebooks. Designed for seamless collaboration with MCP clients including Claude Desktop.

• ⭐ 281
• MCP
• SDGLBL/mcp-claude-code

SonarQube MCP Server offers a Model Context Protocol (MCP) server that integrates with SonarQube, enabling AI assistants to access code quality metrics, issues, and analysis results programmatically. It supports retrieving detailed quality metrics, filtering issues, reviewing security hotspots, analyzing branches and pull requests, and monitoring project health. The server facilitates multi-project analysis, contextual code review, and improved assistant workflows through a standardized protocol.

• ⭐ 101
• MCP
• sapientpants/sonarqube-mcp-server

Implements a Model Context Protocol (MCP) server enabling AI assistants to interact with the Go Language Server Protocol (LSP) for analyzing and understanding Go code. Provides tools for navigation, diagnostics, references, hover info, completion suggestions, and code coverage. Integrates with 'gopls' to deliver precise code intelligence tailored for AI-driven workflows. Designed for seamless integration with platforms that support MCP, including AI development assistants.

• ⭐ 48
• MCP
• hloiseaufcms/mcp-gopls

Codelogic-mcp-server implements an MCP (Model Context Protocol) server, enabling integration of CodeLogic's software dependency data into AI programming assistants. It provides tools for code and database impact assessments by interacting with a CodeLogic server, enhancing context-aware code and database analysis. The server supports integration with popular IDEs, including VS Code and Claude Desktop, using Astral UV/UVX for communication. This solution is designed to bring actionable dependency insights to AI coding workflows.

• ⭐ 31
• MCP
• CodeLogicIncEngineering/codelogic-mcp-server

code-to-tree is an MCP (Model Context Protocol) server that enables large language models to accurately convert source code into abstract syntax trees (AST) across multiple programming languages. It provides a standalone executable that integrates with MCP clients, ensuring seamless parsing using the tree-sitter framework. The server supports languages including C, C++, Rust, Ruby, Go, Java, and Python, with minimal dependencies required. Its design focuses on ease of setup and integration in AI workflows requiring code analysis capabilities.

• ⭐ 66
• MCP
• micl2e2/code-to-tree

Winx Agent is a Rust implementation of WCGW, offering advanced shell execution and file management for large language model code agents. It delivers high-performance, multi-provider AI integration, including automatic fallbacks and code analysis capabilities. Designed for seamless integration with Claude and other LLMs, it leverages the Model Context Protocol (MCP) for standardized context handling. Multiple operational modes, advanced file operations, and interactive shell support make it suitable for robust AI-driven code workflows.

• ⭐ 21
• MCP
• gabrielmaialva33/winx-code-agent