tfmcp: Terraform Model Context Protocol Tool

by nwiizo

370 stars
583 downloads
Not rated
GitHub Website

About

๐ŸŒ Terraform Model Context Protocol (MCP) Tool - An experimental CLI tool that enables AI assistants to manage and operate Terraform environments. Supports reading Terraform configurations, analyzing plans, applying configurations, and managing state with Claude Desktop integrati

Details

Author
nwiizo
GitHub stars
370
Downloads
583
Categories
Developer Tools, Cloud Service

- Deep Terraform CLI integration for analyzing and executing operations
- Runs as a Model Context Protocol server for AI assistants
- Module health analysis with cohesion/coupling metrics and refactoring suggestions
- Resource dependency graph visualization with dot output
- Security scanning with secret detection and configurable policies
- Production-ready audit logging and access restrictions

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

  1. Download and install Highlight from highlightai.com/download
  2. Navigate to the plugins tab and select "Add Custom Plugin"
  3. Configure the plugin with the settings below
    Plugin Name tfmcp: Terraform Model Context Protocol Tool
    Command (node, npx, python, etc.)

    Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.

  4. Enable "Start Automatically" if you want the plugin to start when Highlight launches

From the repository

Install tfmcp with cargo install tfmcp or build from source, then run tfmcp mcp to launch it as an MCP server. To integrate with Claude Desktop, configure ~/Library/Application Support/Claude/claude_desktop_config.json pointing to the tfmcp executable with "args": ["mcp"]. You can specify a Terraform project directory via the -d flag, the TERRAFORM_DIR environment variable, or the set_terraform_directory tool at runtime.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "tfmcp: terraform model context protocol tool": {
            "tfmcp": {
                "command": "docker",
                "args": [
                    "build",
                    "-t",
                    "tfmcp",
                    "."
                ]
            }
        }
    }
}

McpServers

{
    "tfmcp": {
        "command": "docker",
        "args": [
            "build",
            "-t",
            "tfmcp",
            "."
        ]
    }
}
# tfmcp: Terraform Model Context Protocol Tool [![Trust Score](https://archestra.ai/mcp-catalog/api/badge/quality/nwiizo/tfmcp)](https://archestra.ai/mcp-catalog/nwiizo__tfmcp) *โš ๏ธ This project includes production-ready security features but is still under active development. While the security system provides robust protection, please review all operations carefully in production environments. โš ๏ธ* 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: ## ๐ŸŽฎ Demo See tfmcp in action with Claude Desktop: ![tfmcp Demo with Claude Desktop](.github/images/tfmcp-demo.gif) - Reading Terraform configuration files - Analyzing Terraform plan outputs - Applying Terraform configurations - Managing Terraform state - Creating and modifying Terraform configurations ## ๐ŸŽ‰ Latest Release The latest version of tfmcp (v0.1.9) is now available on Crates.io! You can easily install it using Cargo: ```bash cargo install tfmcp ``` ### ๐Ÿ†• What's New in v0.1.9 - **๐Ÿ“Š Plan Analysis**: Structured plan analysis with risk scoring and recommendations - **๐Ÿ” State Analysis**: Deep state inspection with drift detection - **๐Ÿ“ Workspace Management**: Full terraform workspace support (list, show, new, select, delete) - **๐Ÿ“ฅ Import Helper**: Guided resource import with config generation - **โœจ Code Formatting**: terraform fmt integration - **๐Ÿ”— Dependency Graph**: terraform graph visualization with DOT output - **๐Ÿ“ค Output Management**: terraform output access - **๐Ÿท๏ธ Taint/Untaint**: Resource taint management (with deprecation notices for 1.5+) - **๐Ÿ”„ State Refresh**: Explicit state refresh operations - **๐Ÿ“ฆ Provider Info**: Detailed provider information with lock file parsing - **๐Ÿฆ€ Rust Edition 2024**: Migrated to Rust Edition 2024 (requires Rust 1.85.0+) ## Features - ๐Ÿš€ **Terraform Integration** Deeply integrates with the Terraform CLI to analyze and execute operations. - ๐Ÿ“„ **MCP Server Capabilities** Runs as a Model Context Protocol server, allowing AI assistants to access and manage Terraform. - ๐Ÿ”ฌ **Module Health Analysis** Whitebox approach to Infrastructure as Code with cohesion/coupling analysis, health scoring, and refactoring suggestions based on software engineering principles. - ๐Ÿ“Š **Resource Dependency Graph** Visualize resource relationships including explicit depends_on and implicit reference dependencies. - ๐Ÿ“ฆ **Module Registry Integration** Search and explore Terraform modules from the registry, get module details and versions. - ๐Ÿ” **Enterprise Security** Production-ready security controls with configurable policies, audit logging, and access restrictions. - ๐Ÿ“Š **Advanced Analysis** Detailed Terraform configuration analysis with best practice recommendations and security checks. - ๐Ÿ“‹ **Guideline Compliance** (v0.1.8) Future Architect Terraform guidelines integration with compliance scoring, secret detection, and variable quality checks. - โšก๏ธ **Blazing Fast** High-speed processing powered by the Rust ecosystem with optimized parsing and caching. - ๐Ÿ› ๏ธ **Automatic Setup** Automatically creates sample Terraform projects when needed, ensuring smooth operation even for new users. - ๐Ÿณ **Docker Support** Run tfmcp in a containerized environment with all dependencies pre-installed. ## Installation ### From Source ```bash # Clone the repository git clone https://github.com/nwiizo/tfmcp cd tfmcp # Build and install cargo install --path . ``` ### From Crates.io ```bash cargo install tfmcp ``` ### Using Docker ```bash # Clone the repository git clone https://github.com/nwiizo/tfmcp cd tfmcp # Build the Docker image docker build -t tfmcp . # Run the container docker run -it tfmcp ``` ## Requirements - Rust (edition 2021) - Terraform CLI installed and available in PATH - Claude Desktop (for AI assistant integration) - Docker (optional, for containerized deployment) ## Usage ```bash $ tfmcp --help โœจ 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 ``` ### Using Docker When using Docker, you can run tfmcp commands like this: ```bash # Run as MCP server (default) docker run -it tfmcp # Run with specific command and options docker run -it tfmcp analyze --dir /app/example # Mount your Terraform project directory docker run -it -v /path/to/your/terraform:/app/terraform tfmcp --dir /app/terraform # Set environment variables docker run -it -e TFMCP_LOG_LEVEL=debug tfmcp ``` ### Integrating with Claude Desktop To use tfmcp with Claude Desktop: 1. If you haven't already, install tfmcp: ```bash cargo install tfmcp ``` Alternatively, you can use Docker: ```bash docker build -t tfmcp . ``` 2. Find the path to your installed tfmcp executable: ```bash which tfmcp ``` 3. Add the following configuration to `~/Library/Application\ Support/Claude/claude_desktop_config.json`: ```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 } } } } ``` If you're using Docker with Claude Desktop, you can set up the configuration like this: ```json { "mcpServers": { "tfmcp": { "command": "docker", "args": ["run", "--rm", "-v", "/path/to/your/terraform:/app/terraform", "tfmcp", "mcp"], "env": { "TERRAFORM_DIR": "/app/terraform" } } } } ``` 4. Restart Claude Desktop and enable the tfmcp tool. 5. 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. ## MCP Tools tfmcp provides 31 MCP tools for AI assistants: ### Core Terraform Operations | Tool | Description | |------|-------------| | `init_terraform` | Initialize Terraform working directory | | `get_terraform_plan` | Generate and show execution plan | | `analyze_plan` | **NEW** Analyze plan with risk scoring and recommendations | | `apply_terraform` | Apply Terraform configuration | | `destroy_terraform` | Destroy Terraform-managed infrastructure | | `validate_terraform` | Validate configuration syntax | | `validate_terraform_detailed` | Detailed validation with guidelines | | `get_terraform_state` | Show current state | | `analyze_state` | **NEW** Analyze state with drift detection | | `list_terraform_resources` | List all managed resources | | `set_terraform_directory` | Change active project directory | ### Workspace & State (v0.1.9) | Tool | Description | |------|-------------| | `terraform_workspace` | **NEW** Manage workspaces (list, show, new, select, delete) | | `terraform_import` | **NEW** Import existing resources | | `terraform_taint` | **NEW** Taint/untaint resources | | `terraform_refresh` | **NEW** Refresh state | ### Code & Output (v0.1.9) | Tool | Description | |------|-------------| | `terraform_fmt` | **NEW** Format code | | `terraform_graph` | **NEW** Generate dependency graph | | `terraform_output` | **NEW** Get output values | | `terraform_providers` | **NEW** Get provider info with lock file | ### Analysis & Security | Tool | Description | |------|-------------| | `analyze_terraform` | Analyze configuration | | `analyze_module_health` | Module health with cohesion/coupling metrics | | `get_resource_dependency_graph` | Resource dependencies visualization | | `suggest_module_refactoring` | Refactoring suggestions | | `get_security_status` | Security scan with secret detection | ### Registry | Tool | Description | |------|-------------| | `search_terraform_providers` | Search providers | | `get_provider_info` | Provider details | | `get_provider_docs` | Provider documentation | | `search_terraform_modules` | Search modules | | `get_module_details` | Module details | | `get_latest_module_version` | Latest module version | | `get_latest_provider_version` | Latest provider version | ## 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 - **Docker issues**: If using Docker, ensure your container has proper volume mounts and permissions ## Environment Variables ### Core Configuration - `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 Configuration - `TFMCP_ALLOW_DANGEROUS_OPS`: Set to `true` to enable apply/destroy operations (default: `false`) - `TFMCP_ALLOW_AUTO_APPROVE`: Set to `true` to enable auto-approve for dangerous operations (default: `false`) - `TFMCP_MAX_RESOURCES`: Set maximum number of resources that can be managed (default: 50) - `TFMCP_AUDIT_ENABLED`: Set to `false` to disable audit logging (default: `true`) - `TFMCP_AUDIT_LOG_FILE`: Custom path for audit log file (default: `~/.tfmcp/audit.log`) - `TFMCP_AUDIT_LOG_SENSITIVE`: Set to `true` to include sensitive information in audit logs (default: `false`) ## Security Considerations tfmcp includes comprehensive security features designed for production use: ### ๐Ÿ”’ Built-in Security Features - **Access Controls**: Automatic blocking of production/sensitive file patterns - **Operation Restrictions**: Dangerous operations (apply/destroy) disabled by default - **Resource Limits**: Configurable maximum resource count protection - **Audit Logging**: Complete operation tracking with timestamps and user identification - **Directory Validation**: Security policy enforcement for project directories ### ๐Ÿ›ก๏ธ Security Best Practices - **Default Safety**: Apply/destroy operations are disabled by default - explicitly enable only when needed - **Review Plans**: Always review Terraform plans before applying, especially AI-generated ones - **IAM Boundaries**: Use appropriate IAM permissions and role boundaries in cloud environments - **Audit Monitoring**: Regularly review audit logs at `~/.tfmcp/audit.log` - **File Patterns**: Built-in protection against accessing `prod*`, `production*`, and `secret*` patterns - **Docker Security**: When using containers, carefully consider volume mounts and exposed data ### โš™๏ธ Production Configuration ```bash # Recommended production settings export TFMCP_ALLOW_DANGEROUS_OPS=false # Keep disabled for safety export TFMCP_ALLOW_AUTO_APPROVE=false # Require manual approval export TFMCP_MAX_RESOURCES=10 # Limit resource scope export TFMCP_AUDIT_ENABLED=true # Enable audit logging export TFMCP_AUDIT_LOG_SENSITIVE=false # Don't log sensitive data ``` ## Contributing Contributions are welcome! Please feel free to submit a Pull Request. 1. Fork the repository 2. Create your feature branch (`git checkout -b feature/amazing-feature`) 3. Run quality checks before committing: ```bash cargo fmt --all cargo clippy --all-targets --all-features cargo test --all-features ``` 4. Commit your changes (`git commit -m 'Add some amazing feature'`) 5. Push to the branch (`git push origin feature/amazing-feature`) 6. Open a Pull Request ### Release Process Releases are done manually (automated CI release is disabled): 1. Update version in `Cargo.toml` 2. Create GitHub release: `gh release create v0.1.x --title "v0.1.x - Title" --notes "Release notes"` 3. Publish to crates.io: `cargo publish` ## Roadmap Here are some planned improvements and future features for tfmcp: ### Completed - [x] **Basic Terraform Integration** Core integration with Terraform CLI for analyzing and executing operations. - [x] **MCP Server Implementation** Initial implementation of the Model Context Protocol server for AI assistants. - [x] **Automatic Project Creation** Added functionality to automatically create sample Terraform projects when needed. - [x] **Claude Desktop Integration** Support for seamless integration with Claude Desktop. - [x] **Core MCP Methods** Implementation of essential MCP methods including resources/list and prompts/list. - [x] **Error Handling Improvements** Better error handling and recovery mechanisms for robust operation. - [x] **Dynamic Project Directory Switching** Added ability to change the active Terraform project directory without restarting the service. - [x] **Crates.io Publication** Published the package to Crates.io for easy installation via Cargo. - [x] **Docker Support** Added containerization support for easier deployment and cross-platform compatibility. - [x] **Security Enhancements** Comprehensive security system with configurable policies, audit logging, access controls, and production-ready safety features. - [x] **Module Health Analysis (v0.1.6)** Whitebox approach to IaC with cohesion/coupling metrics, health scoring, and refactoring suggestions. - [x] **Resource Dependency Graph (v0.1.6)** Visualization of resource relationships including explicit and implicit dependencies. - [x] **Module Registry Integration (v0.1.6)** Search and explore Terraform modules from the registry. - [x] **Comprehensive Testing Framework** 85+ tests including integration tests with real Terraform configurations. - [x] **RMCP SDK Migration (v0.1.8)** Migrated to official RMCP SDK with proper tool annotations for better MCP compliance. - [x] **Future Architect Guidelines (v0.1.8)** Terraform coding standards compliance checks with secret detection and variable quality validation. ### In Progress - [ ] **Multi-Environment Support** Add support for managing multiple Terraform environments, workspaces, and modules. ### Planned - [ ] **Expanded MCP Protocol Support** Implement additional MCP methods and capabilities for richer integration with AI assistants. - [ ] **Performance Optimization** Optimize resource usage and response times for large Terraform projects. - [ ] **Cost Estimation** Integrate with cloud provider pricing APIs to provide cost estimates for Terraform plans. - [ ] **Interactive TUI** Develop a terminal-based user interface for easier local usage and debugging. - [ ] **Integration with Other AI Platforms** Extend beyond Claude to support other AI assistants and platforms. - [ ] **Plugin System** Develop a plugin architecture to allow extensions of core functionality. ## License This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
No reviews yet โ€” be the first

Sign in to leave a review

Use Google, GitHub, or an email account so ratings stay tied to real people.

Email sign in

No reviews posted yet.