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guilhermeyoshida

MCP Terraform Assistant

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

Related MCP server: Terry-Form MCP

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

A
license - permissive license
-
quality - not tested
D
maintenance

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