tfmcp: Terraform Model Context Protocol Tool

⚠️ This project is experimental. Features may change without notice. Use with caution! ⚠️

tfmcp is a command-line tool that helps you interact with Terraform via the Model Context Protocol (MCP). It allows LLMs to manage and operate your Terraform environments, including:

🎮 Demo

See tfmcp in action with Claude Desktop:

Reading Terraform configuration files
Analyzing Terraform plan outputs
Applying Terraform configurations
Managing Terraform state
Creating and modifying Terraform configurations

🎉 Latest Release

The first stable release of tfmcp (v0.1.1) is now available on Crates.io! You can easily install it using Cargo:

cargo install tfmcp

Features

🚀 Terraform Integration
Deeply integrates with the Terraform CLI to analyze and execute operations.
📄 MCP Server Capabilities
Runs as a Model Context Protocol server, allowing AI assistants to access and manage Terraform.
⚡️ Blazing Fast
High-speed processing powered by the Rust ecosystem.
🛠️ Automatic Setup
Automatically creates sample Terraform projects when needed, ensuring smooth operation even for new users.

Installation

From Source

# Clone the repository
git clone https://github.com/nwiizo/tfmcp
cd tfmcp

# Build and install
cargo install --path .

From Crates.io

cargo install tfmcp

Requirements

Rust (edition 2021)
Terraform CLI installed and available in PATH
Claude Desktop (for AI assistant integration)

Usage

$ tfmcp --help
✨ A CLI tool to manage Terraform configurations and operate Terraform through the Model Context Protocol (MCP).

Usage: tfmcp [OPTIONS] [COMMAND]

Commands:
  mcp       Launch tfmcp as an MCP server
  analyze   Analyze Terraform configurations
  help      Print this message or the help of the given subcommand(s)

Options:
  -c, --config <PATH>    Path to the configuration file
  -d, --dir <PATH>       Terraform project directory
  -V, --version          Print version
  -h, --help             Print help

Integrating with Claude Desktop

To use tfmcp with Claude Desktop:

If you haven't already, install tfmcp:
cargo install tfmcp
Find the path to your installed tfmcp executable:
which tfmcp
Add the following configuration to ~/Library/Application\ Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "tfmcp": {
      "command": "/path/to/your/tfmcp",  // Replace with the actual path from step 2
      "args": ["mcp"],
      "env": {
        "HOME": "/Users/yourusername",  // Replace with your username
        "PATH": "/usr/local/bin:/usr/bin:/bin:/usr/sbin:/sbin",
        "TERRAFORM_DIR": "/path/to/your/terraform/project"  // Optional: specify your Terraform project
      }
    }
  }
}

Restart Claude Desktop and enable the tfmcp tool.
tfmcp will automatically create a sample Terraform project in ~/terraform if one doesn't exist, ensuring Claude can start working with Terraform right away. The sample project is based on the examples included in the example/demo directory of this repository.

Logs and Troubleshooting

The tfmcp server logs are available at:

~/Library/Logs/Claude/mcp-server-tfmcp.log

Common issues and solutions:

Claude can't connect to the server: Make sure the path to the tfmcp executable is correct in your configuration
Terraform project issues: tfmcp automatically creates a sample Terraform project if none is found
Method not found errors: MCP protocol support includes resources/list and prompts/list methods

Environment Variables

TERRAFORM_DIR: Set this to specify a custom Terraform project directory. If not set, tfmcp will use the directory provided by command line arguments, configuration files, or fall back to ~/terraform. You can also change the project directory at runtime using the set_terraform_directory tool.
TFMCP_LOG_LEVEL: Set to debug, info, warn, or error to control logging verbosity.
TFMCP_DEMO_MODE: Set to true to enable demo mode with additional safety features.

Security Considerations

When using tfmcp, please be aware of the following security considerations:

tfmcp executes Terraform commands on your behalf, which can create, modify, or destroy infrastructure
In production environments, consider using appropriate IAM permissions and role boundaries
Review all Terraform plans before applying them, especially when generated by an AI
Sensitive information in your Terraform state might be accessible to the AI assistants

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Fork the repository
Create your feature branch (git checkout -b feature/amazing-feature)
Commit your changes (git commit -m 'Add some amazing feature')
Push to the branch (git push origin feature/amazing-feature)
Open a Pull Request

Roadmap

Here are some planned improvements and future features for tfmcp:

Completed

Basic Terraform Integration
Core integration with Terraform CLI for analyzing and executing operations.
MCP Server Implementation
Initial implementation of the Model Context Protocol server for AI assistants.
Automatic Project Creation
Added functionality to automatically create sample Terraform projects when needed.
Claude Desktop Integration
Support for seamless integration with Claude Desktop.
Core MCP Methods
Implementation of essential MCP methods including resources/list and prompts/list.
Error Handling Improvements
Better error handling and recovery mechanisms for robust operation.
Dynamic Project Directory Switching
Added ability to change the active Terraform project directory without restarting the service.
Crates.io Publication
Published the package to Crates.io for easy installation via Cargo.

In Progress

Enhanced Terraform Analysis
Implement deeper parsing and analysis of Terraform configurations, plans, and state files.
Multi-Environment Support
Add support for managing multiple Terraform environments, workspaces, and modules.
Security Enhancements
Improve security features including better authentication and authorization mechanisms.
Expanded MCP Protocol Support
Implement additional MCP methods and capabilities for richer integration with AI assistants.
Interactive TUI
Develop a terminal-based user interface for easier local usage and debugging.
Cost Estimation
Integrate with cloud provider pricing APIs to provide cost estimates for Terraform plans.
Performance Optimization
Optimize resource usage and response times for large Terraform projects.
Integration with Other AI Platforms
Extend beyond Claude to support other AI assistants and platforms.
Comprehensive Testing Framework
Expand test coverage including integration tests with real Terraform configurations.
Plugin System
Develop a plugin architecture to allow extensions of core functionality.

License

This project is licensed under the MIT License - see the LICENSE file for details.