Context management for Claude Code. Hooks maintain state via ledgers and handoffs. MCP execution without context pollution. Agent orchestration with isolated context windows.

An open source implementation of code execution with MCP (Programatic Tool Calling)

🪐 🤖 AI Agents for JupyterLab with 🔧 MCP tools - Chat interface for optimized notebook interaction and code execution.

MCP server for orchestrating AI coding agents (Claude Code CLI & Gemini CLI). Features task management, process execution, Git integration, and dynamic resource discovery. Full TypeScript implementation with Docker support and Cloudflare Tunnel integration.

Enhanced Claude Code MCP server with orchestration capabilities, reliability improvements, and self-contained execution patterns

A self-hosted AI workspace unifying chat, code execution, parallel multi-agent orchestration, and project management. Each agent runs on a distinct provider — OpenAI-compatible APIs, Claude Code, or Codex CLI. MCP servers extend the toolbox. Built for 100+ tool-call sessions with context compression and checkpoint recovery.

Claude Code plugin: 115 commands, 25 agents, 64 scripts, 67 MCP servers, 143 reference files. Eval/QA layer (hallucination detection, claim verification, A+ through F grading). Multilingual (Sarvam AI, DeepL, Google Cloud Translation). Full execution with approval workflow.

MCP server that gives any LLM its own computer — managed Docker workspaces with live browser, terminal, code execution, document skills, and autonomous sub-agents. Self-hosted, open-source, pluggable into any model.

One stop shop - Local-first RAG stack with intelligent polyglot-code/docs, remote code execution, local llama enrichment, progressive disclosure tools, mcp server, sandboxed security.

Multi-cloud, framwork-agnostic AI agent runtime for building, testing, and deploying production agents across OpenAI, CrewAI, LangGraph, and Google ADK. Deploy the same agent code to AWS or Azure with built-in session management, execution hooks, MCP/A2A support, guardrails, observability and fault tolerance.

MCP server that enables AI assistants to interact with Salesforce orgs through the Salesforce CLI, providing tools for Apex execution, SOQL queries, metadata management, code analysis, and development automation.

The Self-Improving MCP Server - Agents write code to orchestrate multiple MCP servers with intelligent TypeScript execution and auto-augmentation

Code Execution Sandbox Platform Solution for Individuals and Small Teams with MCP

A podman ubuntu 24.04 container that serves a MCP server; with file, code execution, bash shell, knowledgebase, and more.

The fabric-mcp-server is an MCP server that integrates Fabric patterns with AI coding agents and assistants, exposing them as tools for AI-driven task execution and enhancing capabilities.

Autonomous multi-agent AI system with document processing, web automation, and code execution powered by LLM agents and MCP servers

Give your AI agent a wallet, email, phone number, and instant access to paid MCP tools — web search, image/video/music gen, X search, SMS, voice calls, code execution, and more. Works with Gemini CLI, Claude, and any MCP client.

This project provides a comprehensive Kali Linux Docker container with 200+ pentesting tools, optimized for use with Claude Code through a custom skill. By using direct command execution instead of MCP protocol, this system achieves **70% token efficiency** compared to traditional MCP server approaches.

An MCP server that allows AI tools to interact with Claude Code programmatically with session continuity and async execution support.

Context efficient MCP calls with code execution, achieving up to 98.7% token reduction (Inspired by Anthropic Code Execution with MCP)

A secure Python code execution service designed to integrate with LLMs like GPT and Claude, providing a self-hosted alternative to OpenAI's Code Interpreter. Now with MCP server.

A config-driven MCP server core built on the official Rust SDK. Define tools, auth, prompts, resources, and HTTP behavior in YAML or JSON configuration -- the library handles execution, validation, and protocol compliance with minimal Rust code.

Efficient code execution with MCP

A MCP server for secure Python code execution with artifact capture, virtual environment support, and LM Studio integration

On-device AI agent engine for mobile apps — embedded Node.js worker with Claude LLM, file tools, code execution, git, and extensible MCP device tools

MCP server for coordinating multiple Claude Code instances with distributed task execution, unified management, communication, and issue tracking

Experimenting with code execution with MCP using the Claude Agent SDK

Code Intelligence Platform with semantic search, AI-powered transformations, and enterprise security. FastApply MCP Server delivers comprehensive code analysis through local model execution and intelligent pattern recognition.

Docker sandbox for Python/DSPy execution with memvid-backed knowledge store — 16 MCP tools for Claude Code

Langchain agent that generates and executes Python code to interact with Airtable using the MCP code execution pattern from [Anthropic's blog](https://www.anthropic.com/engineering/code-execution-with-mcp).