nkkko/daytona-mcp-interpreter
Built by Metorial, the integration platform for agentic AI.
nkkko/daytona-mcp-interpreter
Server Summary
Execute Python code
Execute shell commands
File management (upload/download)
Clone Git repositories
Generate web previews for running servers
A Model Context Protocol server that provides Python code execution capabilities in ephemeral Daytona sandboxes.
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:
All execution happens in ephemeral Daytona workspaces that are automatically cleaned up after use.
curl -LsSf https://astral.sh/uv/install.sh | sh
If you have an existing env, deactivate and remove it first:
deactivate
rm -rf .venv
Create and activate a new virtual environment:
uv venv
source .venv/bin/activate
(On Windows: .venv\Scripts\activate
)
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.
Configure these environment variables for proper operation:
MCP_DAYTONA_API_KEY
: Required API key for Daytona authenticationMCP_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)Run the server directly:
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:
npx @modelcontextprotocol/inspector \
uv \
--directory . \
run \
src/daytona_mcp_interpreter/server.py
View logs:
tail -f /tmp/daytona-interpreter.log
On MacOS, edit: ~/Library/Application Support/Claude/claude_desktop_config.json
On Windows, edit: %APPDATA%\Claude\claude_desktop_config.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"
}
}
}
}
Executes shell commands in the Daytona workspace.
# Example: List files
ls -la
# Example: Install a package
pip install pandas
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")
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
)
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
)
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:
# 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")