tf-mcp

# Terraform Modules MCP Server A multi-cloud MCP server that lets AI assistants discover, understand, and generate Terraform code from module catalogs across AWS, Azure, and GCP. ## What it does - **Discover modules** — list modules across all clouds with descriptions, dependencies, and costs - **Understand wiring** — see how modules connect (e.g., VPC outputs feed into EKS inputs) - **Estimate costs** — get per-module cost breakdowns by tier (dev/staging/prod) - **Generate code** — produce ready-to-use `.tf` files for single modules or full stacks ## Quick start ### Install via Claude Code Add to your `~/.mcp.json` (global) or `.claude/mcp.json` (per-project): ```json { "mcpServers": { "tf-modules": { "command": "uvx", "args": ["tf-mcp"], "env": { "TF_MODULES_AWS_DIR": "/path/to/your/aws-tf/modules", "TF_MODULES_AZURE_DIR": "/path/to/your/azure-tf/modules", "TF_MODULES_GCP_DIR": "/path/to/your/gcp-tf/modules" } } } } ``` Only include the `env` entries for clouds you have modules for. ### Install via pip ```bash pip install tf-mcp ``` ### Run standalone ```bash tf-mcp ``` ## Prerequisites - Python >= 3.11 - One or more directories containing Terraform modules ## Module directory layout Point the server at directories containing Terraform modules. Each module should be a subdirectory with at least a `main.tf`: ``` your-modules-dir/ vpc/ main.tf variables.tf outputs.tf eks-cluster/ main.tf variables.tf outputs.tf ``` The server auto-discovers all subdirectories containing a `main.tf`. ## Configuration Tell the server where your modules live using environment variables: | Variable | Description | |----------|-------------| | `TF_MODULES_AWS_DIR` | Path to AWS `modules/` directory | | `TF_MODULES_AZURE_DIR` | Path to Azure `modules/` directory | | `TF_MODULES_GCP_DIR` | Path to GCP `modules/` directory | If no env vars are set, the server looks for sibling repo…