Terraform Cloud MCP

🚀 Terraform Cloud MCP Server

The Terraform Cloud MCP Server is a service based on the Model Context Protocol (MCP) for interacting with Terraform Cloud. It offers a variety of tools and features to help users manage and operate their cloud infrastructure.

✨ Features

• Automated Run Management: Achieve automated control of Terraform runs through the MCP protocol.
• Detailed Logging: Debug logging is enabled by default for easy troubleshooting.
• MCP Checker Integration: An in - built checking tool (access URL: http://localhost:5173) for debugging and monitoring.

🚀 Quick Start

📦 Installation

# Clone the repository
git clone https://github.com/severity1/terraform-cloud-mcp.git
cd terraform-cloud-mcp

# Create and activate a virtual environment
uv venv
source .venv/bin/activate  # On Windows, use: .venv\Scripts\activate

# Install dependencies
uv pip install .

Run the Server

# Run the server in development mode
mcp dev terraform_cloud_mcp/server.py

📚 Documentation

Set Up a Quick Development Environment

# Clone the repository
git clone https://github.com/severity1/terraform-cloud-mcp.git
cd terraform-cloud-mcp

# Create and activate a virtual environment
uv venv
source .venv/bin/activate  # On Windows, use: .venv\Scripts\activate

# Install the development version and dependencies
uv pip install -e .
uv pip install black mypy pydantic ruff

Basic Development Commands

# Run the server
mcp dev terraform_cloud_mcp/server.py

# Execute tests and code checks
uv run -m mypy .
uv run -m ruff check .
uv run -m black .

Documentation Resources

• Code Comments: Focus on explaining the "why" behind implementation decisions.
• Docstrings: All public functions and classes include detailed descriptions.
• Example Files:
  • docs/DEVELOPMENT.md: Development standards and programming guidelines.
  • docs/CONTRIBUTING.md: Guidelines for contributing to the project.
  • docs/models/: Usage examples of all model types.
  • docs/tools/: Detailed usage instructions for each tool.
  • docs/conversations/: Example conversation flows for interacting with the API.

💻 Troubleshooting

1. Check the server logs (debug logging is enabled by default).
2. Use the MCP checker for debugging (access URL: http://localhost:5173).
3. Debug logging is enabled in server.py:

   import logging
   logging.basicConfig(level=logging.DEBUG)
   

🤝 Contribution Guidelines

Contributions are welcome! Please participate in the project by submitting issues or pull requests.

For detailed information, please refer to CONTRIBUTING.md to learn how to get started, code quality standards, and the pull - request process.