Terraform MCP Server

The Model Context Protocol (MCP) is an open standard that enables AI models to securely connect with external tools, applications, and data sources. MCP allows AI models to access information beyond their training data, providing more current and accurate responses.

The Terraform MCP server implements this protocol specifically for Terraform development, offering several key benefits:

• Real-time accuracy: Access current provider documentation instead of relying on potentially outdated training data
• Terraform Registry Integration: Direct integration with public Terraform Registry APIs for providers, modules, and policies
• HCP Terraform & Terraform Enterprise Support: Full workspace management, organization/project listing, and private registry access
• Workspace Operations: Create, update, delete workspaces with support for variables, tags, and run management
• AI enhancement: Enables more accurate and actionable Terraform configuration generation

How it works

When you connect an AI model to the Terraform MCP server, the model gains access to specialized tools that can perform the following actions:

1. Search and retrieve current provider documentation
2. Access module information, including inputs, outputs, and examples
3. Find Sentinel policies for governance and compliance
4. HCP Terraform or TFE organization and workspace lists
5. HCP Terraform or TFE workspace, variables, tags, variable set create, read, update and delete operations

The AI model uses these tools automatically when you ask questions about Terraform configuration, ensuring responses are based on the most current information available.