Deploy the Terraform MCP server

The Terraform Model Context Protocol (MCP) server enables AI models to generate Terraform configuration using up-to-date information from the Terraform Registry. This page explains how to install, configure, and integrate the MCP server with your AI client.

Overview

The Terraform MCP server is a specialized service that provides AI models with access to current Terraform provider documentation and module information. You can deploy the server to the following environments:

• Local deployment: Run the server on your workstation using stdio mode for direct communication through standard input/output
• Remote deployment: Run the server on a remote instance using streamable-http mode for network-based communication

Installation methods

Choose from three installation options based on your environment and preferences:

Run in Docker

Docker provides the most reliable and consistent way to run the Terraform MCP server across different environments.

1. Start Docker on your system.
2. Integrate with your AI client:

{
  "mcpServers": {
    "servers": {
      "hcp-terraform": {
        "command": "docker",
        "args": [
          "run",
          "-i",
          "--rm",
          "hashicorp/terraform-mcp-server"
        ]
      }
    }
  }
}

Run the compiled binary

The compiled binary option provides a lightweight installation without Docker dependencies. This method is ideal when you want to minimize resource usage or work in environments with restricted container access.

1. Download the binary for your operating system and architecture, visit the release library.

2. Add the following configuration to your client settings. Replace /path/to/terraform-mcp-server with the actual path to your downloaded binary.

   {
     "mcp": {
       "servers": {
         "terraform": {
           "command": "/path/to/terraform-mcp-server",
           "args": ["stdio"]
         }
       }
     }
   }
   

Install from source

Installing from source gives you access to the latest features and allows for customization. This method requires a Go development environment.

1. Install the latest stable release.

   $ go install github.com/hashicorp/terraform-mcp-server/cmd/terraform-mcp-server@latest
   

   Alternatively, you can install the development version on main.

   $ go install github.com/hashicorp/terraform-mcp-server/cmd/terraform-mcp-server@main
   

2. After installation, add the following configuration to your client.

   {
     "mcp": {
       "servers": {
         "terraform": {
           "command": "/path/to/terraform-mcp-server",
           "args": ["stdio"]
         }
       }
     }
   }
   

   Replace /path/to/terraform-mcp-server with the actual path to your downloaded binary. The binary location depends on your Go installation and GOPATH configuration.

   Use which terraform-mcp-server to find the installed binary path.

Start the server

You can use the terraform-mcp-server CLI and specify the transport protocol you want to use to start the server. Refer to the transport protocols reference for more information.

Start the server in stdio mode.

$ terraform-mcp-server stdio [--log-file /path/to/log]

Run the following command on the local instance to start the server in streamable-http mode:

$ terraform-mcp-server streamable-http \
  [--transport-port 8080] \
  [--transport-host 127.0.0.1] \
  [--mcp-endpoint /mcp] \
  [--log-file /path/to/log]

Instead of setting values manually, you can also use the supported environment variables. Refer to the environment variables reference for details.

Next steps

• Begin prompting your AI model about Terraform configurations. Refer to Prompt an AI model for guidance on effective prompting techniques.
• The server provides access to up-to-date provider documentation.
• Ask for help with specific Terraform resources and modules.
• Explore advanced configuration options for your specific deployment needs.