Mcp Code Executor Server

Name: Mcp Code Executor Server
Author: mouadenna

@mouadenna

Repository

About Mcp Code Executor Server

dedicated isolated environment for your AI agent

Basic information

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "mcp-code-executor-server": {
      "command": "docker",
      "args": [
        "build",
        "-t",
        "mcp-code-executor",
        "."
      ]
    }
  }
}

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Mcp Code Executor Server?

Mcp Code Executor Server is a Model Context Protocol (MCP) server that enables AI agents to execute code across multiple programming languages in a secure, isolated environment. It standardizes how AI models connect to various programming runtimes by exposing a unified MCP tool endpoint. The server is for developers integrating code execution capabilities into AI workflows.

How to use Mcp Code Executor Server?

Clone the repository, build with ./mvnw clean package, and start the server with ./mvnw spring-boot:run. The server listens on port 8080 by default. Alternatively, run via Docker using docker build -t mcp-code-executor . and docker run -p 8080:8080 mcp-code-executor. Connect an MCP-compatible AI client to http://localhost:8080 and invoke the code-execution tool with a JSON payload specifying language and code.

Key features of Mcp Code Executor Server

Multi-language support: Java, Python, JavaScript, TypeScript, C++
Secure execution in isolated containers with resource limits
MCP integration for seamless client discovery
Automatic compilation for Java, C++, and TypeScript
Detailed compile-time and runtime error feedback
Automatic cleanup of temporary files and execution timeouts

Use cases of Mcp Code Executor Server

AI assistants executing code snippets in a sandboxed environment
Automated testing of code in multiple languages from a single interface
Providing AI agents with runtime feedback to refine code generation
Enabling multi-language code evaluation in educational AI tools
Integrating code execution into MCP-compatible client workflows

FAQ from Mcp Code Executor Server

Which programming languages are supported?

Java, Python, JavaScript, TypeScript, and C++.

How does the server ensure secure code execution?

It uses isolated containers with resource limits on CPU, memory, and timeouts, and automatically deletes temporary files.

What are the prerequisites to run the server locally?

Java 17+, Python 3.8+, Node.js & npm, and a C++ compiler (g++).

Can I run the server in a container for additional isolation?

Yes, the README provides Docker and Docker Compose instructions for running the server in a container.

How do I connect an MCP client to the server?

Start your MCP-compatible AI client and point it to http://localhost:8080 to discover and invoke the code-execution tool.

Comments

More Developer Tools MCP servers

FastAPI-MCP

tadata-org

Expose your FastAPI endpoints as Model Context Protocol (MCP) tools, with Auth!

11.9K

TalkToFigma

sonnylazuardi

TalkToFigma: MCP integration between AI Agent (Cursor, Claude Code, Codex) and Figma, allowing Agentic AI to communicate with Figma for reading designs and modifying them programmatically.

6.9K