Provides tools for interacting with Terraform Cloud API, enabling management and monitoring of workspaces, runs, and their statuses across organizations.
Terraform Cloud MCP Server
Model Context Protocol server providing Terraform Cloud API integration as tools for AI assistants.
Features
This MCP server exposes four main tools for interacting with Terraform Cloud:
get_run_status: Get current run status and recent runs for a workspace
list_workspaces: List all workspaces in an organization
get_workspace_details: Get detailed information about a specific workspace
get_run_details: Get detailed information about a specific run by its ID
Installation
Configuration
The server reads your Terraform Cloud token from ~/.terraform.d/credentials.tfrc.json. Make sure this file exists with the following format:
Usage
With Claude Desktop
Add to your Claude Desktop configuration (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):
With MCP Inspector
Test your server with the MCP Inspector:
With VS Code
Create a .vscode/mcp.json file in your project:
Available Tools
get_run_status
Get the current run status for a Terraform Cloud workspace.
Parameters:
workspaceName(string, required): Name of the workspaceorganization(string, optional): Organization name (default: "urbanmedia")
Example:
list_workspaces
List all workspaces in a Terraform Cloud organization.
Parameters:
organization(string, optional): Organization name (default: "urbanmedia")
Example:
get_workspace_details
Get detailed information about a specific workspace.
Parameters:
workspaceName(string, required): Name of the workspaceorganization(string, optional): Organization name (default: "urbanmedia")
Example:
get_run_details
Get detailed information about a specific Terraform Cloud run by its ID.
Parameters:
runId(string, required): Run ID (e.g., "run-abc123")
Example:
Development
Project Structure
Running in Development
Building
License
MIT
This server cannot be installed
hybrid server
The server is able to function both locally and remotely, depending on the configuration or use case.
Enables AI assistants to interact with Terraform Cloud workspaces and runs, including checking run status, listing workspaces, and retrieving detailed information about workspaces and runs.