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Terraform Mcp Server By Binadox

Terraform Mcp Server By Binadox

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github.com/binadox-publicCloud & Infra1Updated 52w ago

About Terraform Mcp Server By Binadox

Binadox’s Terraform MCP server validates and completes Terraform configurations, checks security, and estimates cloud costs. It is for users generating or modifying infrastructure code through MCP clients, with AWS security checks and cost analysis for AWS, Azure, and GCP.

Key features

  1. 01Validate and complete Terraform configurations
  2. 02Detect common security misconfigurations
  3. 03Estimate monthly cloud resource costs
  4. 04Organize output into files and modules
  5. 05Provide cost data for AWS, Azure, and GCP

Use cases

  1. 01Generate runnable Terraform configurations
  2. 02Check infrastructure security before deployment
  3. 03Estimate monthly costs for proposed cloud resources

MCP support

The server exposes Terraform preparation, analysis, and cost-estimation tools to MCP clients. Security checks cover AWS, while Azure and GCP are supported for cost analysis.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

Terraform MCP Server by Binadox

MCP server for Terraform — automatically validates, secures, and estimates cloud costs for Terraform configurations. Developed by Binadox, it integrates with any Model Context Protocol (MCP) client (e.g. Claude Desktop or other MCP-compatible AI assistants).


Table of Contents


Overview

The Binadox Terraform MCP Server is an MCP (Model Context Protocol) server that helps large language models (LLMs) safely generate Terraform infrastructure code with built-in cost estimation and security checks before deployment.

It acts as a bridge between your AI assistant and Terraform: when your LLM needs to produce or modify cloud infrastructure code, this server augments the AI’s response with structured tooling (validation, linting, security analysis, cost data) instead of relying solely on the model’s guesses. This ensures the Terraform configuration you get is more complete, secure, and cost-aware from the start.

Learn more about how to manage Terraform-driven infrastructure with our tool here: Binadox IaC Cost Tracker.


Features

  • Code validation & completion – Processes Terraform snippets and fills in missing parts (providers, versions, variables) for a runnable configuration.
  • Security analysis – Detects common misconfigurations and insecure defaults (open ports, missing encryption, etc.) in the generated code.
  • Cost estimation – Computes a monthly cloud cost breakdown for the proposed resources using real pricing data.
  • File organization – Organizes output into logical Terraform files/modules (e.g. groups resources into modules, adds terraform.tfvars if needed).
  • Easy integration – Works with any MCP-compatible client (tested with Claude Desktop) for seamless use in your AI-driven workflow.

Compatibility & Requirements

ComponentSupported / Tested Version
Go1.22+
Terraform CLI1.6+
CloudsAWS (full: cost + checks), Azure & GCP (cost only, checks in roadmap)
MCP ClientsClaude Desktop (tested), other MCP-compatible clients

Prerequisites

  • Go toolchain (if building from source)
  • Terraform CLI 1.6+ installed
  • Valid Binadox API token
  • Internet access to Binadox pricing API
  • Write access to /tmp/terraform/...

Installation

To install binadox-terraform-mcp, clone the repository and build the binary with Go. Then, add the executable path to your Claude Desktop configuration file claude_desktop_config.json under the mcpServers section, including your Binadox API URL and token. Finally, restart Claude Desktop to apply the changes and start using the Terraform MCP server.

  1. Clone and build:
git clone https://github.com/binadox/binadox-terraform-mcp
cd binadox-terraform-mcp
go build -o terraform-mcp-server *.go
  1. Configure your MCP client (example: Claude Desktop)
# Add to Claude Desktop config
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%\Claude\claude_desktop_config.json
{
  "mcpServers": {
    "terraform": {
      "command": "/path/to/terraform-mcp-server",
      "env": {
        "TERRAFORM_ANALYSIS_URL": "https://app.binadox.com/api/1/organizations/pricing/terraform/mcp",
        "TERRAFORM_ANALYSIS_TOKEN": "your-token"
      }
    }
  }
}
  1. Restart your MCP client to apply the configuration.

Usage

No additional CLI commands are required. Once installed and configured, the server operates behind the scenes to:

  • Validate and complete Terraform code via prepare_terraform
  • Analyze for misconfigurations via analyze_terraform
  • Estimate cloud costs via calculate_cost

All output files are written to /tmp/terraform/<timestamp> and zipped if needed.


Examples

Cost Overrun Prevention
User: Generate terraform for a simple demo environment

Cost Analysis: $1,847/month
- m5.2xlarge instances
- Multi-AZ RDS
- NAT Gateways in 3 AZs
Security Misconfiguration Detection
User: Create an RDS database with a security group

Security Analysis:
- 0.0.0.0/0 open access
- No encryption at rest
- 1-day backup retention
Completing Incomplete Configurations
User: Add resource "aws_s3_bucket" "data" { bucket = "my-data" }

Without MCP: Fails – no provider block  
With MCP: Adds provider, variables, and metadata – configuration runs

Security & Privacy

The server runs locally and does not access cloud credentials.

  • Files are saved under /tmp/terraform/ and are not sent externally.
  • Only cost data is requested remotely using your Binadox token.
  • No telemetry or analytics are collected.

API Requirements

Cost analysis requires a Binadox API token. Binadox provides real-time cloud pricing data across AWS, Azure, and GCP. Get your token at Binadox.


Documentation


License

Apache 2.0

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.