"Debugging and Navigating Code in a Project" matching MCP servers:

Gemini-powered MCP server for automated code review, analysis, and documentation.

An MCP server that scaffolds full-stack projects with consistent structure, Docker setup, CI/CD pipelines, and database configuration.

An MCP server that bridges multiple LLMs (OpenAI-compatible APIs and CLI coding agents) for collaborative debugging and diverse AI perspectives.

Enables AI agents to control NetEase Cloud Music playback, login, search, and get personalized recommendations through official APIs.

Bridges a local AI agent to a Colab session in the browser, enabling code execution and file operations through the Model Context Protocol.

An MCP server for debugging Temporal workflows, enabling LLM-assisted inspection of workflow executions, detailed workflow info, and event history.

An OpenOCD debug MCP server that manages debugging targets and sessions by reusing VS Code launch configurations. It enables firmware flashing, GDB command execution, and real-time status monitoring of embedded systems.

A comprehensive development toolkit with 23 tools covering code quality analysis, development efficiency, and project management. Enables AI-assisted code review, test generation, performance analysis, SQL generation, UI component creation, and automated project documentation.

A template and demonstration project for building, testing, and deploying remote MCP servers using FastMCP and uv. It provides a foundational structure for creating MCP-compliant tools that can be hosted publicly and integrated with LLM agents.

AutoHotkey v2 MCP Server with prompts, tool chains, debugging, and code execution.

Enables code execution in 70+ programming languages and databases through the Onecompiler API, allowing users to run and test code directly from their MCP-enabled applications.

A personal memory engine and MCP server that stores durable facts in markdown files managed via git, enabling hybrid search (lexical + semantic) through an MCP interface for persistent context across LLM sessions.

Enables querying git commit history to analyze when and why code changes happened, providing authorship context and diffs for specific modules.

Sandboxed Python execution with automatic dependency management. Executes Python scripts in isolated environments (bubblewrap or Docker) with PEP 723 inline dependencies, preventing host pollution.

A secure MCP server that stores and retrieves API keys and credentials, featuring encrypted storage, masked retrieval, and AI-powered recommendation via MCP sampling.

Code-mode MCP server (docs_search + execute_code two-tool surface) backed by a unified capability manifest across three sandbox kernels (in-process node:vm, WASM via QuickJS / Pyodide / Wasmtime, and remote microVM via E2B / Cloudflare Sandbox). At N=30 tools the bootstrap-context cost drops to 13.6% of direct tool-use. Apache-2.0.

Enables AI assistants to query, analyze, and discover FileMaker database schemas via OData v4, with pandas-powered analytics for efficient data summaries.

Enables AI assistants to render 3D models from OpenSCAD code, generating single views or multiple perspectives with full camera control. Supports animations, custom parameters, and returns base64-encoded PNG images for seamless integration.

MCP server that enables cloud models (like Gemini/Claude) to delegate coding tasks to a local llama.cpp server, preserving cloud usage limits through an AI-powered code review loop.

Enables Claude to speak in 70+ languages, including pronunciation, audio flashcards, and full language lessons with tutor personas.