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

Clone the repository:

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

Install dependencies using uv:

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

Docker Installation

Clone the repository:

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

Build and run the Docker container:
```
docker-compose up -d
```

Usage

Local Usage

Start the MCP server:
```
python main.py
```

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

Start the MCP server:
```
docker-compose up -d
```

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

Fork the repository
Create a feature branch
Commit your changes
Push to the branch
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:

Start the MCP server:
```
python main.py
```
Connect to the server using an MCP client:
```
mcp connect http://localhost:8000
```
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