MCP Infrastructure as Code Assistant
About
An MCP server for managing infrastructure as code using Terraform
Details
- Author
- guilhermeyoshida
- Downloads
- 167
- Categories
- Cloud Service
Jump to
- Initialize Terraform working directories
- Generate and show execution plans
- Apply and destroy infrastructure changes
- Validate Terraform configurations
- Show current state or saved plans
- Manage Terraform workspaces
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
MCP Infrastructure as Code AssistantCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Install using Python 3.8+ and Terraform 1.5.7+, either locally via uv or using Docker Compose. Start the server with python main.py or docker-compose up -d, then use the MCP CLI to call tools like mcp terraform_init or mcp terraform_apply.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"mcp infrastructure as code assistant": {
"mcp-terraform-assistant": {
"command": "uv",
"args": [
"pip",
"install",
"-e",
"."
]
}
}
}
}McpServers
{
"mcp-terraform-assistant": {
"command": "uv",
"args": [
"pip",
"install",
"-e",
"."
]
}
}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
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