# Code Execution

The PHP MCP protocol server is used to integrate PHP with Anthropic's Claude AI, supporting direct execution of PHP code and providing environment information.

The Code Runner MCP Server is an MCP service that supports the execution of multi - language code snippets. It can directly run code and display results in applications such as VS Code.

JupyterMCP is a tool that integrates Jupyter Notebook with Claude AI via the Model Context Protocol (MCP). It supports functions such as bidirectional communication, cell operations, and code execution, and is only compatible with Jupyter Notebook version 6.x.

This is a server that implements the MCP code execution mode. Through a single-tool bridge and zero-context discovery mechanism, it reduces the overhead of MCP tool calls from tens of thousands of tokens to about 200 tokens and securely executes Python code in the root container, supporting data science and secure isolation.

This is a project configured with an MCP code runner server, supporting code execution in a container or virtual machine environment.

The Dumpling AI MCP Server is a model context protocol server integrating multiple AI functions, providing capabilities such as data scraping, content processing, knowledge management, AI agents, and code execution.

The YepCode MCP Server is a server implementing the Model Context Protocol. It can transform YepCode processes into AI tools, supports remote and local deployment, and provides functions such as code execution, environment management, and process execution.

The MCP service for Emacs, supporting the generation and execution of Elisp code

An MCP protocol service implemented in Python that provides a standardized API to execute Python code

An MCP server that provides a Python interactive interpreter, supporting persistent sessions and package management

The MCP Python Interpreter is a service that allows LLMs to interact with a Python environment, providing functions such as code execution, file operations, and package management, and supporting multiple development workflows.

CodeBox-AI is a secure Python code execution service that provides self-hosted code interpreter functionality, supports conversational code execution, dynamic package installation, and visual output, and integrates the MCP protocol for interaction with LLM applications.

A Docker - based MCP server that can execute multi - language code in isolated containers and return results, supporting dependency management and container management.

This is a prototype of a code execution server based on the MCP protocol, which combines the code generation capabilities of large language models with MCP tool integration, enabling AI agents to run Python code in an isolated sandbox and invoke external tools.

Riza provides a secure code interpreter service, offering an isolated execution environment for LLM-generated code through the MCP server.

CodeSavant is a code management server based on the MCP protocol, providing code reading, writing, execution, and version control functions, supporting multi - language development and historical backtracking.

The Daytona MCP interpreter is a server that implements the Model Context Protocol (MCP) standard, providing AI assistants with the ability to execute Python code and Shell commands in a secure isolated environment.

This project is a multi - tool integration and code execution platform based on FastMCP. It supports importing MCP tools from local and SSE clients, provides Docker deployment and streaming code execution management, and is suitable for various tool invocation scenarios such as chemical information query and web page parsing.

The MCP Code Executor is a server that allows LLMs to execute Python code in a specified Conda environment.

PRIMS is a lightweight open - source MCP server designed for LLM agents, providing a secure one - time Python code sandbox execution environment that supports dependency installation and file mounting.

Nash MCP is a multi - functional command execution server that supports Shell command execution, Python code execution, web content fetching, and task management, providing secure credential storage and session management functions.

A secure MCP server that allows AI assistants to execute TypeScript and JavaScript code through the Deno runtime, with configurable permission control and lightweight characteristics.

An MCP server that provides stateful Django shell interaction for AI assistants, allowing direct execution of Python code in a Django project and maintaining session state

A Docker-based FastMCP server that provides a secure code execution, Shell command, and multi-language running environment for AI agents, supporting integration with Claude Desktop and Cursor

The Go Playground MCP server is a tool integrated with the Go Playground API that can execute Go code and generate shareable URL links through the MCP protocol