Daytona MCP Python Interpreter

# Daytona MCP Interpreter A Model Context Protocol server that provides Python code execution capabilities in ephemeral Daytona sandboxes.  ## Overview Daytona MCP Interpreter enables AI assistants like Claude to execute Python code and shell commands in secure, isolated environments. It implements the Model Context Protocol (MCP) standard to provide tools for: - Python code execution in sandboxed environments - Shell command execution - File management (upload/download) - Git repository cloning - Web preview generation for running servers All execution happens in ephemeral Daytona workspaces that are automatically cleaned up after use. ## Installation 1. Install uv if you haven't already: ```bash curl -LsSf https://astral.sh/uv/install.sh | sh ``` 2. Create and activate virtual environment. If you have an existing env, deactivate and remove it first: ```bash deactivate rm -rf .venv ``` Create and activate a new virtual environment: ```bash uv venv source .venv/bin/activate ``` (On Windows: `.venv\Scripts\activate`) 3. Install dependencies: ```bash uv add "mcp[cli]" pydantic python-dotenv "daytona-sdk>=0.10.5" ``` > Note: This project requires daytona-sdk version 0.10.5 or higher. Earlier versions have incompatible FileSystem API. ## Environment Variables Configure these environment variables for proper operation: - `MCP_DAYTONA_API_KEY`: Required API key for Daytona authentication - `MCP_DAYTONA_SERVER_URL`: Server URL (default: https://app.daytona.io/api) - `MCP_DAYTONA_TIMEOUT`: Request timeout in seconds (default: 180.0) - `MCP_DAYTONA_TARGET`: Target region (default: eu) - `MCP_VERIFY_SSL`: Enable SSL verification (default: false) ## Development Run the server directly: ```bash uv run src/daytona_mcp_interpreter/server.py ``` Or if uv is not in your path: ``` /Users/USER/.local/bin/uv run ~LOCATION/daytona-mcp-interpreter/src/daytona_mcp_interpreter/server.py ``` Use MCP Inspector to test the server: ```bash npx @modelcontextprotocol/inspector \ uv \ --directory . \ run \ src/daytona_mcp_interpreter/server.py ``` View logs: ``` tail -f /tmp/daytona-interpreter.log ``` ## Integration with Claude Desktop [](https://youtu.be/26m2MjY8a5c) 1. Configure in Claude Desktop (or other MCP-compatible clients): On MacOS, edit: `~/Library/Application Support/Claude/claude_desktop_config.json` On Windows, edit: `%APPDATA%\Claude\claude_desktop_config.json` ```json { "mcpServers": { "daytona-interpreter": { "command": "/Users/USER/.local/bin/uv", "args": [ "--directory", "/Users/USER/dev/daytona-mcp-interpreter", "run", "src/daytona_mcp_interpreter/server.py" ], "env": { "PYTHONUNBUFFERED": "1", "MCP_DAYTONA_API_KEY": "api_key", "MCP_DAYTONA_SERVER_URL": "api_server_url", "MCP_DAYTONA_TIMEOUT": "30.0", "MCP_VERIFY_SSL": "false", "PATH": "/usr/local/bin:/usr/bin:/bin:/usr/sbin:/sbin" } } } } ``` 2. Restart Claude Desktop 3. The Daytona Python interpreter tools will be available in Claude ## Available Tools ### Shell Exec Executes shell commands in the Daytona workspace. ```bash # Example: List files ls -la # Example: Install a package pip install pandas ``` ### File Download Downloads files from the Daytona workspace with smart handling for large files. **Basic Usage:** ``` file_download(file_path="/path/to/file.txt") ``` **Advanced Usage:** ``` # Set custom file size limit file_download(file_path="/path/to/large_file.csv", max_size_mb=10.0) # Download partial content for large files file_download(file_path="/path/to/large_file.csv", download_option="download_partial", chunk_size_kb=200) # Convert large file to text file_download(file_path="/path/to/large_file.pdf", download_option="convert_to_text") # Compress file before downloading file_download(file_path="/path/to/large_file.bin", download_option="compress_file") # Force download despite size file_download(file_path="/path/to/large_file.zip", download_option="force_download") ``` ### File Upload Uploads files to the Daytona workspace. Supports both text and binary files. **Basic Usage:** ``` # Upload a text file file_upload(file_path="/workspace/example.txt", content="Hello, World!") ``` **Advanced Usage:** ``` # Upload a text file with specific path file_upload( file_path="/workspace/data/config.json", content='{"setting": "value", "enabled": true}' ) # Upload a binary file using base64 encoding import base64 with open("local_image.png", "rb") as f: base64_content = base64.b64encode(f.read()).decode('utf-8') file_upload( file_path="/workspace/images/uploaded.png", content=base64_content, encoding="base64" ) # Upload without overwriting existing files file_upload( file_path="/workspace/important.txt", content="New content", overwrite=False ) ``` ### Git Clone Clones a Git repository into the Daytona workspace for analysis and code execution. **Basic Usage:** ``` git_clone(repo_url="https://github.com/username/repository.git") ``` **Advanced Usage:** ``` # Clone a specific branch git_clone( repo_url="https://github.com/username/repository.git", branch="develop" ) # Clone to a specific directory with full history git_clone( repo_url="https://github.com/username/repository.git", target_path="my_project", depth=0 # 0 means full history ) # Clone with Git LFS support for repositories with large files git_clone( repo_url="https://github.com/username/large-files-repo.git", lfs=True ) ``` ### Web Preview Generates a preview URL for web servers running inside the Daytona workspace. **Basic Usage:** ``` # Generate a preview link for a web server running on port 3000 web_preview(port=3000) ``` **Advanced Usage:** ``` # Generate a preview link with a descriptive name web_preview( port=8080, description="React Development Server" ) # Generate a link without checking if server is running web_preview( port=5000, check_server=False ) ``` **Example:** ```bash # First run a simple web server using Python via the shell shell_exec(command="python -m http.server 8000 &") # Then generate a preview link for the server web_preview(port=8000, description="Python HTTP Server") ``` <a href="https://glama.ai/mcp/servers/hj7jlxkxpk"><img width="380" height="200" src="https://glama.ai/mcp/servers/hj7jlxkxpk/badge" alt="Daytona Python Interpreter MCP server" /></a> [](https://smithery.ai/server/@nkkko/daytona-mcp)