mcp-terraform-assistant

mcp-terraform-assistant

1
cloud_platformsos_automation

The MCP Infrastructure as Code Assistant is a server designed to manage infrastructure as code using Terraform. It provides functionalities for initializing, planning, applying, and validating Terraform configurations, as well as managing Terraform workspaces.

MCP Infrastructure as Code Assistant

An MCP server for managing infrastructure as code with Terraform.

Features

  • Initialize Terraform working directories
  • Generate and show execution plans
  • Apply changes to infrastructure
  • Destroy infrastructure
  • Validate Terraform configurations
  • Show current state or saved plans
  • Manage Terraform workspaces

Prerequisites

  • Python 3.8 or higher
  • Terraform 1.5.7 or higher
  • Docker and Docker Compose (optional)

Installation

Local Installation

  1. Clone the repository:

    git clone https://github.com/yourusername/mcp-iac.git
cd mcp-iac

  2. Install dependencies using uv:

    curl -LsSf https://astral.sh/uv/install.sh | sh
uv pip install -e .

Docker Installation

  1. Clone the repository:

    git clone https://github.com/yourusername/mcp-iac.git
cd mcp-iac

  2. Build and run the Docker container:

    docker-compose up -d

Usage

Local Usage

  1. Start the MCP server:

    python main.py

  2. Use the MCP CLI to interact with the server:

    mcp terraform_init --working-dir ./terraform
mcp terraform_plan --working-dir ./terraform
mcp terraform_apply --working-dir ./terraform --auto-approve

Docker Usage

  1. Start the MCP server:

    docker-compose up -d

  2. Use the MCP CLI to interact with the server:

    mcp terraform_init --working-dir ./terraform
mcp terraform_plan --working-dir ./terraform
mcp terraform_apply --working-dir ./terraform --auto-approve

Example Terraform Configuration

The repository includes an example Terraform configuration that creates an EC2 instance in AWS:

terraform {
  required_providers {
    aws = {
      source  = "hashicorp/aws"
      version = "~> 5.0"
    }
  }
}

provider "aws" {
  region = var.region
}

resource "aws_instance" "example" {
  ami           = var.ami_id
  instance_type = var.instance_type

  tags = {
    Name = var.instance_name
  }
}

Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Commit your changes
  4. Push to the branch
  5. Create a Pull Request

License

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

Available Tools

  • terraform_init: Initialize a Terraform working directory
  • terraform_plan: Generate and show an execution plan for Terraform
  • terraform_apply: Apply the changes required to reach the desired state
  • terraform_destroy: Destroy the infrastructure managed by Terraform
  • terraform_validate: Validate the syntax and internal consistency of Terraform files
  • terraform_show: Show the current state or a saved plan
  • terraform_workspace_list: List Terraform workspaces
  • terraform_workspace_select: Select a Terraform workspace

Example Usage

Here's an example of how to use the MCP server with an AI agent:

  1. Start the MCP server:

    python main.py

  2. Connect to the server using an MCP client:

    mcp connect http://localhost:8000

  3. The AI agent can now help you with Terraform operations. For example:

    • Initialize a Terraform working directory
    • Generate and review execution plans
    • Apply changes to infrastructure
    • Destroy infrastructure resources
    • Validate Terraform configurations

Examples

Check out the examples directory for sample Terraform configurations that demonstrate how to use the MCP server:

  • examples/aws-s3: A simple AWS S3 bucket example