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MCP Code Executor Server

@mouadenna

リポジトリ

基本情報

カテゴリ

開発者ツール

ライセンス

MIT license

トランスポート

stdio

作者

mouadenna

MCP Code Executor Server について

dedicated isolated environment for your AI agent

MCP Code Executor Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

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

MCP Code Executor Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

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

よくある質問

1

Which programming languages are supported?

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

2

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.

3

What are the prerequisites to run the server locally?

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

4

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.

5

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.

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