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Coala Runtime

An MCP (Model Context Protocol) server for executing Python and R scripts in containerized environments with support for dynamic package installation and file mounting.

Features

  • Containerized Execution: Run Python and R scripts in isolated Docker containers
  • Dynamic Package Installation:
    • Python: Uses uv for fast package installation
    • R: Uses r2u and BiocManager for CRAN and Bioconductor packages
  • File Mounting: Bind-mount local files and directories into containers
  • Pre-installed packages: Python image includes numpy, pandas, matplotlib; R image includes tidyverse
  • MCP Integration: Exposes coala_python_executor and coala_r_executor tools for LLM interaction

Prerequisites

Installation

# Install dependencies
uv pip install -e .

# Or using pip
pip install -e .

Docker Images

By default, the server pulls the executor images from Docker Hub if they are not present locally:

  • hubentu/coala-runtime-python:latest → tagged as coala-runtime-python:latest
  • hubentu/coala-runtime-r:latest → tagged as coala-runtime-r:latest

To build the images locally instead (e.g. for development or custom Dockerfiles), run with --build or build manually:

coala-runtime --build
# or
python -m coala_runtime --build

Manual build (same as --build):

./docker/build.sh

This creates:

  • coala-runtime-python:latest - Python executor image
  • coala-runtime-r:latest - R executor image

Usage

As MCP Server

The server can be run as an MCP server for LLM integration:

coala-runtime

Or with the module runner:

python -m coala_runtime

Use coala-runtime --build (or python -m coala_runtime --build) to build Docker images locally before starting.

Configuration

See MCP_CONFIG.md for detailed configuration instructions for various MCP clients (Cursor, Claude Desktop, etc.).

Tool Schemas

coala_python_executor

Executes Python scripts in a containerized environment with uv package management.

Input:

  • script or script_file (one required): Inline Python code or host path to a .py file
  • packages (optional): Additional packages to install via uv. The image already includes numpy, pandas, matplotlib. Can include version specifiers (e.g., 'requests>=2.31.0')
  • conda_packages (optional, Python only): Conda specs installed before pip/uv (requires conda/mamba in the image)
  • docker_image (optional): Docker image to run instead of the default Coala Python image (e.g. python:3.12-slim, quay.io/biocontainers/...)
  • skip_package_install (optional): If true, skip install step (typical when docker_image already has all dependencies)
  • input_files (optional): Map of container paths to host paths for bind-mounting (e.g., {'/input/data.csv': '/host/path/data.csv'})
  • timeout (optional): Execution timeout in seconds (default: 300, 0 = no timeout, max: 3600)

Output:

  • success: Whether execution succeeded
  • exit_code: Process exit code (0 = success)
  • stdout: Standard output from script
  • stderr: Standard error output
  • output_files: List of output file paths (for files/images generated by the script)
  • output_data: Echoed output for strings/numbers (captured via print statements)
  • container_logs: Full container execution logs including package installation
  • execution_time: Execution time in seconds

coala_r_executor

Executes R scripts in a containerized environment with r2u and BiocManager.

Input:

  • script or script_file (one required): Inline R code or host path to an .R file
  • packages (optional): Additional R packages to install. Use 'bioc::package_name' format for Bioconductor packages. The image already includes tidyverse. Examples: ['ggplot2', 'dplyr', 'bioc::Biobase']
  • docker_image (optional): Docker image to run instead of the default Coala R image (must provide Rscript on PATH)
  • skip_package_install (optional): If true, skip install step (typical when docker_image already has all dependencies)
  • input_files (optional): Map of container paths to host paths for bind-mounting (e.g., {'/input/data.csv': '/host/path/data.csv'})
  • timeout (optional): Execution timeout in seconds (default: 300, 0 = no timeout, max: 3600)

Output: Same as coala_python_executor

Development

# Install with dev dependencies
uv pip install -e ".[dev]"

# Run tests
pytest

# Format code
black src tests

# Lint code
ruff check src tests

License

MIT

Release files for coala-runtime 0.1.0

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