38 Repos
Tools for code analysis, execution, IDE integration, and software development workflows.
Explore 38 awesome GitHub repositories matching part of an awesome list · Development & Execution. Refine with filters or upvote what's useful.
Context7 is an AI-powered documentation retrieval engine designed to provide developers and AI agents with real-time, context-aware access to technical documentation and code snippets. By integrating external library documentation as callable tools, the platform equips AI coding assistants with project-specific knowledge, helping to improve generation accuracy and reduce hallucinations during inference. The platform distinguishes itself through a robust security and governance framework that manages documentation as a centralized knowledge base. It employs a multi-source ingestion pipeline to
Real-time library documentation and code example injection.
Serena is a static site generator designed to transform markdown files into structured, navigable documentation websites. It functions as a documentation engine that processes source content into pre-rendered HTML pages, providing a clean and organized reading experience for technical manuals and knowledge bases. The platform distinguishes itself through a component-based layout framework that injects parsed content into reusable templates to maintain design consistency. It also features a built-in client-side search engine that constructs local databases, allowing users to retrieve informati
Coding agent with language server-based symbol operations.
This project serves as an educational resource and implementation guide for the Model Context Protocol. It provides developers with the patterns and documentation necessary to standardize how large language models interact with external systems, local data sources, and various services. The repository focuses on facilitating the translation of technical documentation and educational materials into multiple languages. By utilizing an AI assistant integration framework, it enables the creation of localized learning resources that help developers master complex programming concepts regardless of
Educational resources for learning MCP development.
git-mcp is a Model Context Protocol server that transforms Git repositories and static sites into structured context providers for AI assistants. It functions as a documentation retrieval tool and repository indexer, exposing codebases and project files as standardized tools to reduce hallucinations in large language model responses. The project converts raw repository files, READMEs, and external URLs into formats optimized for token consumption. It enables AI agents to perform query-based code searches and retrieve specific sections of project documentation to maintain up-to-date technical
Remote access to GitHub repositories and documentation.
DesktopCommanderMCP is a Model Context Protocol (MCP) server that gives AI agents direct access to local files, shell commands, and system processes through natural language instructions. It acts as a unified bridge between conversational commands and desktop operations, enabling an AI to translate plain English into file management, code editing, system command execution, data analysis, and software scaffolding tasks without needing its own API. The server exposes these capabilities as structured tools via the MCP protocol, so any compatible agent can interact with the local environment in a
File system, search, and coding command utilities.
Magic MCP is a Model Context Protocol server and AI component generator that translates natural language descriptions into functional user interface code. It acts as an LLM design orchestrator, producing responsive web elements and layouts anchored on utility-first CSS styling patterns. The system features a side-by-side variation engine that generates multiple stylistic interpretations of a single prompt for comparative selection. It incorporates SVG-based asset integration for branding and iconography and utilizes template-based assembly to combine pre-defined style patterns with user-speci
Integration for creating UI components.
Control what your AI can see. LeanCTX (Lean Context) is the context intelligence layer for AI agents — one local Rust binary that decides what they read, remembers what they learn, guards what they touch, and proves what they save. 60–90% fewer tokens as the receipt. 76 MCP tools, 30+ agents, local-first.
Context runtime for coding agents with session caching.
Coding assistant MCP for Claude Desktop
Basic file and command-line coding agent.
A model context protocol server to work with JetBrains IDEs: IntelliJ, PyCharm, WebStorm, etc. Also, works with Android Studio
Proxy for connecting AI agents to JetBrains IDEs.
A model context protocol server to work with JetBrains IDEs: IntelliJ, PyCharm, WebStorm, etc. Also, works with Android Studio
Direct integration for code operations in JetBrains IDEs.
A flexible HTTP fetching Model Context Protocol server.
Flexible JSON, text, and HTML data retrieval.
An MCP server for interacting with Sentry via LLMs.
Error monitoring and performance issue analysis integration.
A MCP server for using Semgrep to scan code for security vulnerabilities.
Automated code security scanning integration.
mem0-mcp-server wraps the official Mem0 Memory API as a Model Context Protocol (MCP) server so any MCP-compatible client (Claude Desktop, Cursor, custom agents) can add, search, update, and delete long-term memories.
Memory and preference management for coding assistants.
Audit-grade multi-agent orchestration for CLI coding agents (Claude Code, Codex, Gemini CLI, +40 more). HMAC-chained audit log, signed agent cards, per-artefact lineage, air-gap deploy. The orchestrator your compliance team will sign off on. https://bernstein.run
Multi-agent orchestrator for parallel coding workflows.
MCP server for document format conversion using pandoc.
Document format conversion using Pandoc.
Semantic code searcher and codebase utility
Semantic code indexing and GraphRAG knowledge graph construction.
Giving Claude ability to run code with E2B via MCP (Model Context Protocol)
Cloud-based secure code execution sandbox.
An MCP server to create secure code sandbox environment for executing code within Docker containers. This MCP server provides AI applications with a safe and isolated environment for running code while maintaining security through containerization.
Docker-based isolated code execution.
Analyzes your codebase identifying important files based on dependency relationships. Generates diagrams and importance scores per file, helping AI assistants understand the codebase. Automatically parses popular programming languages such as Python, C, C++, Rust, Zig, Lua.
Codebase dependency analysis and structure visualization.