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MCP-Terraform-assistant
Ein MCP -Server zur Verwaltung der Infrastruktur als Code mit Terraform
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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
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Reviews

user_cFCj9opy
As a dedicated user of the mcp-terraform-assistant by guilhermeyoshida, I find this tool incredibly useful for managing my Terraform configurations. Its intuitive design and comprehensive features have significantly improved my infrastructure deployment process. Highly recommend it for anyone looking to streamline their Terraform tasks! Check it out on GitHub: https://github.com/guilhermeyoshida/mcp-terraform-assistant.