Terraform MCP Server

The Terraform MCP Server is a Model Context Protocol (MCP) server that provides seamless integration with Terraform Registry APIs, enabling advanced automation and interaction capabilities for Infrastructure as Code (IaC) development.

Features

• Dual Transport Support: Both Stdio and StreamableHTTP transports
• Terraform Provider Discovery: Query and explore Terraform providers and their documentation
• Module Search & Analysis: Search and retrieve detailed information about Terraform modules
• Registry Integration: Direct integration with Terraform Registry APIs
• Container Ready: Docker support for easy deployment

Caution: The outputs and recommendations provided by the MCP server are generated dynamically and may vary based on the query, model, and the connected MCP server. Users should thoroughly review all outputs/recommendations to ensure they align with their organization's security best practices, cost-efficiency goals, and compliance requirements before implementation.

Security Note: When using the StreamableHTTP transport in production, always configure the MCP_ALLOWED_ORIGINS environment variable to restrict access to trusted origins only. This helps prevent DNS rebinding attacks and other cross-origin vulnerabilities.

Prerequisites

1. To run the server in a container, you will need to have Docker installed.
2. Once Docker is installed, you will need to ensure Docker is running.

Transport Support

The Terraform MCP Server supports multiple transport protocols:

1. Stdio Transport (Default)

Standard input/output communication using JSON-RPC messages. Ideal for local development and direct integration with MCP clients.

2. StreamableHTTP Transport

Modern HTTP-based transport supporting both direct HTTP requests and Server-Sent Events (SSE) streams. This is the recommended transport for remote/distributed setups.

Features:

• Endpoint: http://{hostname}:8080/mcp
• Health Check: http://{hostname}:8080/health
• Environment Configuration: Set TRANSPORT_MODE=http or TRANSPORT_PORT=8080 to enable

Environment Variables:

Command Line Options

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

# StreamableHTTP mode
terraform-mcp-server streamable-http [--transport-port 8080] [--transport-host 127.0.0.1] [--mcp-endpoint /mcp] [--log-file /path/to/log]

Session Modes

The Terraform MCP Server supports two session modes when using the StreamableHTTP transport:

• Stateful Mode (Default): Maintains session state between requests, enabling context-aware operations.
• Stateless Mode: Each request is processed independently without maintaining session state, which can be useful for high-availability deployments or when using load balancers.

To enable stateless mode, set the environment variable:

export MCP_SESSION_MODE=stateless

Installation# Usage with VS Code

Add the following JSON block to your User Settings (JSON) file in VS Code. You can do this by pressing Ctrl + Shift + P and typing Preferences: Open User Settings (JSON).

More about using MCP server tools in VS Code's agent mode documentation.

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

Optionally, you can add a similar example (i.e. without the mcp key) to a file called .vscode/mcp.json in your workspace. This will allow you to share the configuration with others.

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

Usage with Claude Desktop / Amazon Q Developer / Amazon Q CLI

More about using MCP server tools in Claude Desktop user documentation. Read more about using MCP server in Amazon Q from the documentation.

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

Tool Configuration# Available Toolsets

The following sets of tools are available:

Resource Configuration# Available resources

Available Resource Templates

Install from source

Use the latest release version:

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

Use the main branch:

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

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

Building the Docker Image locally

Before using the server, you need to build the Docker image locally:

1. Clone the repository:

git clone https://github.com/hashicorp/terraform-mcp-server.git
cd terraform-mcp-server

2. Build the Docker image:

make docker-build

3. This will create a local Docker image that you can use in the following configuration.

docker run -i --rm terraform-mcp-server:dev

# Run in streamable-http mode
docker run -p 8080:8080 --rm -e TRANSPORT_MODE=streamable-http -e TRANSPORT_HOST=0.0.0.0 terraform-mcp-server:dev

Note: When running in Docker, you should set TRANSPORT_HOST=0.0.0.0 to allow connections from outside the container.

4. (Optional) Test connection in http mode

curl http://localhost:8080/health

5. You can use it on your AI assistant as follow:

{
  "mcpServers": {
    "terraform": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "terraform-mcp-server:dev"
      ]
    }
  }
}

Development# Prerequisites

• Go (check go.mod file for specific version)
• Docker (optional, for container builds)

Available Make Commands

Contributing

1. Fork the repository
2. Create your feature branch
3. Make your changes
4. Run tests
5. Submit a pull request

License

This project is licensed under the terms of the MPL-2.0 open source license. Please refer to LICENSE file for the full terms.

Security

For security issues, please contact [email protected] or follow our security policy.

Support

For bug reports and feature requests, please open an issue on GitHub.

For general questions and discussions, open a GitHub Discussion.