The Terraform MCP Server is aModel Context Protocol (MCP)server that provides seamless integration with Terraform Registry APIs, enabling advancedautomation and interaction capabilities for Infrastructure as Code (IaC) development.

• Dual Transport Support: Both Stdio and StreamableHTTP transports with configurable endpoints
• 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

Security Note: At this stage, the MCP server is intended for local use only. If using the StreamableHTTP transport, always configure the MCP_ALLOWED_ORIGINS environment variable to restrict access to trusted origins only. This helps prevent DNS rebinding attacks and other cross-origin vulnerabilities.

Security Note: Depending on the query, the MCP server may expose certain Terraform data to the MCP client and LLM. Do not use the MCP server with untrusted MCP clients or LLMs.

Legal Note: Your use of a third party MCP Client/LLM is subject solely to the terms of use for such MCP/LLM, and IBM is not responsible for the performance of such third party tools. IBM expressly disclaims any and all warranties and liability for third party MCP Clients/LLMs, and may not be able to provide support to resolve issues which are caused by the third party tools.

Caution: The outputs and recommendations provided by the MCP server are generated dynamically and may vary based on the query, model, and the connected MCP client. Users should thoroughly review all outputs/recommendations to ensure they align with their organization’s security best practices, cost-efficiency goals, and compliance requirements before implementation.

1. EnsureDocker is installed and running to use the server in a containerized environment.
2. Install an AI assistant that supports the Model Context Protocol (MCP).

Environment Variables:

# Stdio modeterraform-mcp-server stdio [--log-file /path/to/log]# StreamableHTTP modeterraform-mcp-server streamable-http [--transport-port 8080] [--transport-host 127.0.0.1] [--mcp-endpoint /mcp] [--log-file /path/to/log]

Default instructions for the MCP server is located incmd/terraform-mcp-server/instructions.md, if those do not seem appropriate for your organization's Terraform practices or if the MCP server is producing inaccurate responses, please replace them with your own instructions and rebuild the container or binary. An example of such instruction is located ininstructions/example-mcp-instructions.md

AGENTS.md essentially behaves as READMEs for coding agents: a dedicated, predictable place to provide the context and instructions to help AI coding agents work on your project. OneAGENTS.md file works with different coding agents. An example of such instruction is located ininstructions/example-AGENTS.md, in order to use it commit a file nameAGENTS.md to the directory where your Terraform configurations reside.

Add the following JSON block to your User Settings (JSON) file in VS Code. You can do this by pressingCtrl + Shift + P and typingPreferences: Open User Settings (JSON).

More about using MCP server tools in VS Code'sagent mode documentation.

{"mcp": {"servers": {"terraform": {"command":"docker","args": ["run","-i","--rm","-e","TFE_TOKEN=${input:tfe_token}","-e","TFE_ADDRESS=${input:tfe_address}","hashicorp/terraform-mcp-server:0.3.0"        ]      }    },"inputs": [      {"type":"promptString","id":"tfe_token","description":"Terraform API Token","password":true      },      {"type":"promptString","id":"tfe_address","description":"Terraform Address","password":false      }    ]  }}

{"mcp": {"servers": {"terraform": {"command":"docker","args": ["run","-i","--rm","hashicorp/terraform-mcp-server:0.2.3"        ]      }    }  }}

Optionally, you can add a similar example (i.e. without the mcp key) to a file called.vscode/mcp.json in your workspace. This will allow you to share the configuration with others.

{"servers": {"terraform": {"command":"docker","args": ["run","-i","--rm","-e","TFE_TOKEN=${input:tfe_token}","-e","TFE_ADDRESS=${input:tfe_address}","hashicorp/terraform-mcp-server:0.3.0"      ]    }  },"inputs": [    {"type":"promptString","id":"tfe_token","description":"Terraform API Token","password":true    },    {"type":"promptString","id":"tfe_address","description":"Terraform Address","password":false    }  ]}

{"servers": {"terraform": {"command":"docker","args": ["run","-i","--rm","hashicorp/terraform-mcp-server:0.2.3"      ]    }  }}

Add this to your Cursor config (~/.cursor/mcp.json) or via Settings → Cursor Settings → MCP:

{"mcpServers": {"terraform": {"command":"docker","args": ["run","-i","--rm","-e","TFE_ADDRESS=<<PASTE_TFE_ADDRESS_HERE>>","-e","TFE_TOKEN=<<PASTE_TFE_TOKEN_HERE>>","hashicorp/terraform-mcp-server:0.3.0"      ]    }  }}

{"servers": {"terraform": {"command":"docker","args": ["run","-i","--rm","hashicorp/terraform-mcp-server:0.2.3"      ]    }  }}

More about using MCP server tools in Claude Desktopuser documentation. Read more about using MCP server in Amazon Q from thedocumentation.

{"mcpServers": {"terraform": {"command":"docker","args": ["run","-i","--rm","-e","TFE_ADDRESS=<<PASTE_TFE_ADDRESS_HERE>>","-e","TFE_TOKEN=<<PASTE_TFE_TOKEN_HERE>>","hashicorp/terraform-mcp-server:0.3.0"      ]    }  }}

{"mcpServers": {"terraform": {"command":"docker","args": ["run","-i","--rm","hashicorp/terraform-mcp-server:0.2.3"      ]    }  }}

More about using and adding MCP server tools in Claude Codeuser documentation

• Local (stdio) Transport

claude mcp add terraform -s user -t stdio -- docker run -i --rm hashicorp/terraform-mcp-server

• Remote (streamable-http) Transport

# Run server (example)docker run -p 8080:8080 --rm -e TRANSPORT_MODE=streamable-http -e TRANSPORT_HOST=0.0.0.0 hashicorp/terraform-mcp-server# Add to Claude Codeclaude mcp add --transport http terraform http://localhost:8080/mcp

For security, avoid hardcoding your credentials, create or update~/.gemini/.env (where ~ is your home or project directory) for storing HCP Terraform or Terraform Enterprise credentials

# ~/.gemini/.envTFE_ADDRESS=your_tfe_address_hereTFE_TOKEN=your_tfe_token_here

Install the extension & run Gemini

gemini extensions install https://github.com/hashicorp/terraform-mcp-servergemini

Use the latest release version:

go install github.com/hashicorp/terraform-mcp-server/cmd/terraform-mcp-server@latest

Use the main branch:

go install github.com/hashicorp/terraform-mcp-server/cmd/terraform-mcp-server@main

{"mcp": {"servers": {"terraform": {"type":"stdio","command":"/path/to/terraform-mcp-server","env": {"TFE_TOKEN":"<<TFE_TOKEN_HERE>>"        },      }    }  }}

{"mcp": {"servers": {"terraform": {"type":"stdio","command":"/path/to/terraform-mcp-server"      }    }  }}

Before using the server, you need to build the Docker image locally:

1. Clone the repository:

git clone https://github.com/hashicorp/terraform-mcp-server.gitcd terraform-mcp-server

2. Build the Docker image:

make docker-build

3. This will create a local Docker image that you can use in the following configuration.

# Run in stdio modedocker run -i --rm terraform-mcp-server:dev# Run in streamable-http modedocker run -p 8080:8080 --rm -e TRANSPORT_MODE=streamable-http -e TRANSPORT_HOST=0.0.0.0 terraform-mcp-server:dev

Note: When running in Docker, you should setTRANSPORT_HOST=0.0.0.0 to allow connections from outside the container.

4. (Optional) Test connection in http mode

# Test the connectioncurl http://localhost:8080/health

5. You can use it on your AI assistant as follow:

{"mcpServers": {"terraform": {"command":"docker","args": ["run","-i","--rm","terraform-mcp-server:dev"      ]    }  }}

Check out available tools here 🔗

Check out available resources here 🔗

The Terraform MCP Server supports multiple transport protocols:

Standard input/output communication using JSON-RPC messages. Ideal for local development and direct integration with MCP clients.

Modern HTTP-based transport supporting both direct HTTP requests and Server-Sent Events (SSE) streams. This is the recommended transport for remote/distributed setups.

Features:

• Endpoint:http://{hostname}:8080/mcp
• Health Check:http://{hostname}:8080/health
• Environment Configuration: SetTRANSPORT_MODE=http orTRANSPORT_PORT=8080 to enable

The Terraform MCP Server supports two session modes when using the StreamableHTTP transport:

• Stateful Mode (Default): Maintains session state between requests, enabling context-aware operations.
• Stateless Mode: Each request is processed independently without maintaining session state, which can be useful for high-availability deployments or when using load balancers.

To enable stateless mode, set the environment variable:

export MCP_SESSION_MODE=stateless

• Go (checkgo.mod file for specific version)
• Docker (optional, for container builds)

1. Fork the repository
2. Create your feature branch
3. Make your changes
4. Run tests
5. Submit a pull request

This project is licensed under the terms of the MPL-2.0 open source license. Please refer toLICENSE file for the full terms.

For security issues, please contactsecurity@hashicorp.com or follow oursecurity policy.

For bug reports and feature requests, please open an issue on GitHub.

For general questions and discussions, open a GitHub Discussion.

Terraform

Byhashicorp·979

Seamlessly integrate with Terraform ecosystem, enabling advanced automation and interaction capabilities for Infrastructure as Code (IaC) development powered by Terraform