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Terraform MCP server overview

The Terraform Model Context Protocol (MCP) server enhances AI models with real-time access to current Terraform provider documentation, modules, and policies from the Terraform registry. This ensures AI-generated Terraform configurations use accurate, up-to-date information rather than potentially outdated training data.

Note

This feature is currently in beta. Do not use beta functionality in production environments.

What is the 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  • Real-time accuracy: Access current provider documentation instead of relying on potentially outdated training data
  • Registry integration: Direct connection to the official Terraform registry
  • Comprehensive coverage: Support for providers, modules, and Sentinel policies
  • 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

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

The server specifically handles registry-based information. For general Terraform questions or code generation requests not requiring registry data, AI models use their standard training data and other sources.

Additional resources

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