Integrates with Terraform Cloud API to enable natural language management of infrastructure through workspace and run op...
Created byApr 23, 2025
Terraform Cloud MCP Server
A Model Context Protocol (MCP) server that integrates AI assistants with the Terraform Cloud API, allowing you to manage your infrastructure through natural conversation. Built with Pydantic models and structured around domain-specific modules, this server is compatible with any MCP-supporting platform including Claude, Claude Code CLI, Claude Desktop, Cursor, Copilot Studio, and others.
Replace `your_terraform_cloud_token` with your actual Terraform Cloud API token.
Other MCP-Compatible Platforms
For other platforms (like Cursor, Copilot Studio, or Glama), follow their platform-specific instructions for adding an MCP server. Most platforms require:
The server path or command to start the server.
Environment variables for the Terraform Cloud API token.
Configuration to auto-start the server when needed.
Available Tools
Account Tools
`get_account_details()`: Gets account information for the authenticated user or service account.
Workspace Management Tools
List & Search
`list_workspaces(organization, page_number, page_size, search)`: List and filter workspaces.
`get_workspace_details(workspace_id, organization, workspace_name)`: Get detailed information about a specific workspace.
Create & Update
`create_workspace(organization, name, params)`: Create a new workspace with optional parameters.
`update_workspace(organization, workspace_name, params)`: Update an existing workspace's configuration.
Delete
`delete_workspace(organization, workspace_name)`: Delete a workspace and all its content.
`safe_delete_workspace(organization, workspace_name)`: Delete only if the workspace isn't managing any resources.
Lock & Unlock
`lock_workspace(workspace_id, reason)`: Lock a workspace to prevent runs.
`unlock_workspace(workspace_id)`: Unlock a workspace to allow runs.
`force_unlock_workspace(workspace_id)`: Force unlock a workspace locked by another user.
Run Management Tools
`create_run(workspace_id, params)`: Create and queue a Terraform run in a workspace using its ID.
`list_runs_in_workspace(workspace_id, ...)`: List and filter runs in a specific workspace using its ID.
`list_runs_in_organization(organization, ...)`: List and filter runs across an entire organization.
`get_run_details(run_id)`: Get detailed information about a specific run.
`apply_run(run_id, comment)`: Apply a run waiting for confirmation.
`discard_run(run_id, comment)`: Discard a run waiting for confirmation.
`cancel_run(run_id, comment)`: Cancel a run currently planning or applying.
`force_cancel_run(run_id, comment)`: Forcefully cancel a run immediately.
`force_execute_run(run_id)`: Forcefully execute a pending run by canceling prior runs.
Plan Management Tools
`get_plan_details(plan_id)`: Get detailed information about a specific plan.
`get_plan_json_output(plan_id)`: Retrieve the JSON execution plan for a specific plan with proper redirect handling.
`get_run_plan_json_output(run_id)`: Retrieve the JSON execution plan from a run with proper redirect handling.
Apply Management Tools
`get_apply_details(apply_id)`: Get detailed information about a specific apply.
`get_errored_state(apply_id)`: Retrieve the errored state from a failed apply for recovery.
Organization Management Tools
`get_organization_details(organization)`: Get detailed information about a specific organization.
`get_organization_entitlements(organization)`: Show entitlement set for organization features.
`list_organizations(page_number, page_size, query, query_email, query_name)`: List and filter organizations.
`create_organization(name, email, params)`: Create a new organization with optional parameters.
`update_organization(organization, params)`: Update an existing organization's settings.
`delete_organization(organization)`: Delete an organization and all its content.
Development Guide
For detailed development guidance including code standards, Pydantic patterns, and contribution workflows, see our [Development Documentation](docs/DEVELOPMENT.md).
Quick Development Setup
Basic Development Commands
For detailed information on code organization, architecture, development workflows, and code quality guidelines, refer to [docs/DEVELOPMENT.md](docs/DEVELOPMENT.md).
Documentation
The codebase includes comprehensive documentation:
**Code Comments**: Focused on explaining the "why" behind implementation decisions
**Docstrings**: All public functions and classes include detailed docstrings
**Example Files**: The `docs/` directory contains detailed examples for each domain:
- `docs/DEVELOPMENT.md`: Development standards and coding guidelines
- `docs/CONTRIBUTING.md`: Guidelines for contributing to the project
- `docs/models/`: Usage examples for all model types
- `docs/tools/`: Detailed usage examples for each tool
- `docs/conversations/`: Sample conversation flows with the API
Troubleshooting
Check server logs (debug logging is enabled by default)
Use the MCP Inspector (http://localhost:5173) for debugging
Debug logging is already enabled in `server.py`:
```python
import logging
logging.basicConfig(level=logging.DEBUG)
```
Contributing
Contributions are welcome! Please open an issue or pull request if you'd like to contribute to this project.
See our [Contributing Guide](docs/CONTRIBUTING.md) for detailed instructions on how to get started, code quality standards, and the pull request process.