📌Overview

Purpose: The MCP Code Executor enables LLMs to execute Python code within a defined Conda environment, providing access to necessary libraries and dependencies.

Overview: The MCP Code Executor is a server designed to facilitate the execution of Python code generated from LLM prompts. It operates within a specified Conda environment, ensuring that the necessary libraries and dependencies are accessible during code execution, thus allowing for seamless execution and integration of Python scripts.

Key Features:

Execute Python code from LLM prompts: Allows LLMs to directly run code they generate, enhancing their functionality and interactivity.
Run code within a specified Conda environment: Ensures all dependencies and libraries required for execution are available, thereby increasing reliability and versatility of code execution.
Configurable code storage directory: Users can specify where generated code files should be stored, offering flexibility and organization in managing code outputs.

MCP Code Executor

The MCP Code Executor is an MCP server that allows LLMs to execute Python code within a specified Conda environment. This enables LLMs to run code with access to libraries and dependencies defined in the Conda environment.

Features

Execute Python code from LLM prompts
Run code within a specified Conda environment
Configurable code storage directory

Prerequisites

Node.js installed
Conda installed
Desired Conda environment created

Setup

Clone this repository:

git clone https://github.com/bazinga012/mcp_code_executor.git

Navigate to the project directory:

cd mcp_code_executor

Install the Node.js dependencies:

npm install

Build the project:

npm run build

Configuration

To configure the MCP Code Executor server, add the following to your MCP servers configuration file:

{
  "mcpServers": {
    "mcp-code-executor": {
      "command": "node",
      "args": [
        "/path/to/mcp_code_executor/build/index.js" 
      ],
      "env": {
        "CODE_STORAGE_DIR": "/path/to/code/storage",
        "CONDA_ENV_NAME": "your-conda-env"
      }
    }
  }
}

Replace the placeholders:

/path/to/mcp_code_executor with the absolute path to where you cloned this repository
/path/to/code/storage with the directory where you want the generated code to be stored
your-conda-env with the name of the Conda environment you want the code to run in

Usage

Once configured, the MCP Code Executor will allow LLMs to execute Python code by generating a file in the specified CODE_STORAGE_DIR and running it within the Conda environment defined by CONDA_ENV_NAME.

LLMs can generate and execute code by referencing this MCP server in their prompts.

Contributing

Contributions are welcome! Please open an issue or submit a pull request.

License

This project is licensed under the MIT License.