https://github.com/bazinga012/mcp_code_executor
The MCP Code Executor is an MCP server that allows LLMs to execute Python code within a specified Conda environment.
https://github.com/bazinga012/mcp_code_executor
Last synced: 25 days ago
JSON representation
The MCP Code Executor is an MCP server that allows LLMs to execute Python code within a specified Conda environment.
- Host: GitHub
- URL: https://github.com/bazinga012/mcp_code_executor
- Owner: bazinga012
- License: mit
- Created: 2025-02-06T15:58:32.000Z (2 months ago)
- Default Branch: master
- Last Pushed: 2025-03-20T04:07:12.000Z (about 1 month ago)
- Last Synced: 2025-03-20T05:20:36.005Z (about 1 month ago)
- Language: JavaScript
- Size: 18.6 KB
- Stars: 27
- Watchers: 1
- Forks: 5
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# MCP Code Executor
[](https://smithery.ai/server/@bazinga012/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
1. Clone this repository:
```bash
git clone https://github.com/bazinga012/mcp_code_executor.git
```
2. Navigate to the project directory:
```bash
cd mcp_code_executor
```
3. Install the Node.js dependencies:
```bash
npm install
```
4. Build the project:
```bash
npm run build
```
## Configuration
To configure the MCP Code Executor server, add the following to your MCP servers configuration file:
```json
{
"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.