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thrashr888

Terraform Registry MCP Server

Publisherthrashr888
Repositoryterraform-mcp-server
LanguageTypeScript
Forks
20
Stars
120
Available tools
10
Transport typestdio, streamable-http
Categories
LicenseMIT
Links
  • Connect tools to AI workflows

    Terraform Registry exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 10 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    120 stars and 20 forks from the linked repository.

Terraform Registry MCP Server

A Model Context Protocol (MCP) server that provides tools for interacting with the Terraform Registry API. This server enables AI agents to query provider information, resource details, and module metadata.

[!IMPORTANT] This project was used as a PoC for a new official Terraform MCP server. This repo has been archived in favor of that one.

Installation

Installing in Cursor

To install and use this MCP server in Cursor:

  1. In Cursor, open Settings (⌘+,) and navigate to the "MCP" tab.

  2. Click "+ Add new MCP server."

  3. Enter the following:

    • Name: terraform-registry
    • Type: command
    • Command: npx -y terraform-mcp-server
  4. Click "Add" then scroll to the server and click "Disabled" to enable the server.

  5. Restart Cursor, if needed, to ensure the MCP server is properly loaded.

terraform-registry MCP settings for Cursor

Installing in Claude Desktop

To install and use this MCP server in Claude Desktop:

  1. In Claude Desktop, open Settings (⌘+,) and navigate to the "Developer" tab.

  2. Click "Edit Config" at the bottom of the window.

  3. Edit the file (~/Library/Application Support/Claude/claude_desktop_config.json) to add the following code, then Save the file.

json
{
  "mcpServers": {
    "terraform-registry": {
      "command": "npx",
      "args": ["-y", "terraform-mcp-server"]
    }
  }
}
  1. Restart Claude Desktop to ensure the MCP server is properly loaded.

Tools

The following tools are available in this MCP server:

Core Registry Tools

ToolDescription
providerDetailsGets detailed information about a Terraform provider
resourceUsageGets example usage of a Terraform resource and related resources
moduleSearchSearches for and recommends Terraform modules based on a query
listDataSourcesLists all available data sources for a provider and their basic details
resourceArgumentDetailsFetches comprehensive details about a resource type's arguments
moduleDetailsRetrieves detailed metadata for a Terraform module
functionDetailsGets details about a Terraform provider function
providerGuidesLists and views provider-specific guides and documentation
policySearchSearches for policy libraries in the Terraform Registry
policyDetailsGets detailed information about a specific policy library

Terraform Cloud Tools

These tools require a Terraform Cloud API token (TFC_TOKEN):

ToolDescription
listOrganizationsLists all organizations the authenticated user has access to
privateModuleSearchSearches for private modules in an organization
privateModuleDetailsGets detailed information about a private module
explorerQueryQueries the Terraform Cloud Explorer API to analyze data
listWorkspacesLists workspaces in an organization
workspaceDetailsGets detailed information about a specific workspace
lockWorkspaceLocks a workspace to prevent runs
unlockWorkspaceUnlocks a workspace to allow runs
listRunsLists runs for a workspace
runDetailsGets detailed information about a specific run
createRunCreates a new run for a workspace
applyRunApplies a run that's been planned
cancelRunCancels a run that's in progress
listWorkspaceResourcesLists resources in a workspace

Resources

The MCP server supports the following resource URIs for listing and reading via the resources/* methods:

Resource TypeExample URI(s)Description
Providersterraform:providersList all namespaces/providers
terraform:provider:<namespace>/<name>Get details for a specific provider
Provider Versionsterraform:provider:<namespace>/<name>/versionsList available versions for a provider
Provider Resourcesterraform:provider:<namespace>/<name>/resourcesList resources for a provider
terraform:resource:<namespace>/<name>/<resource_name>Get details for a specific resource type
Provider Data Sourcesterraform:provider:<namespace>/<name>/dataSourcesList data sources for a provider
terraform:dataSource:<namespace>/<name>/<data_source_name>Get details for a specific data source
Provider Functionsterraform:provider:<namespace>/<name>/functionsList functions for a provider
terraform:function:<namespace>/<name>/<function_name>Get details for a specific function

The server also supports resources/templates/list to provide templates for creating:

  • terraform:provider
  • terraform:resource
  • terraform:dataSource

Prompts

The following prompts are available for generating contextual responses:

PromptDescriptionRequired Arguments
migrate-cloudsGenerate Terraform code to migrate infrastructure between cloud providerssourceCloud, targetCloud, terraformCode
generate-resource-skeletonHelps users quickly scaffold new Terraform resources with best practicesresourceType
optimize-terraform-moduleProvides actionable recommendations for improving Terraform codeterraformCode
migrate-provider-versionAssists with provider version upgrades and breaking changesproviderName, currentVersion, targetVersion, terraformCode (optional)
analyze-workspace-runsAnalyzes recent run failures and provides troubleshooting guidance for Terraform Cloud workspacesworkspaceId, runsToAnalyze (optional, default: 5)

Known Issues with Prompts

Note: There is a known issue with the getPrompt functionality that can cause server crashes. The server properly registers prompts and can list them, but direct requests using the getPrompt method may cause connectivity issues. This is being investigated and may be related to SDK compatibility or implementation details. Until resolved, use listPrompts to see available prompts but avoid direct getPrompt calls.

Running the Server

The server runs using stdio transport for MCP communication:

bash
npm install
npm start

Configuration with Environment Variables

The server can be configured using environment variables:

Environment VariableDescriptionDefault Value
TERRAFORM_REGISTRY_URLBase URL for Terraform Registry APIhttps://registry.terraform.io
DEFAULT_PROVIDER_NAMESPACEDefault namespace for providershashicorp
LOG_LEVELLogging level (error, warn, info, debug)info
REQUEST_TIMEOUT_MSTimeout for API requests in milliseconds10000
RATE_LIMIT_ENABLEDEnable rate limiting for API requestsfalse
RATE_LIMIT_REQUESTSNumber of requests allowed in time window60
RATE_LIMIT_WINDOW_MSTime window for rate limiting in milliseconds60000
TFC_TOKENTerraform Cloud API token for private registry access (optional)

Example usage with environment variables:

bash
# Set environment variables
export LOG_LEVEL="debug"
export REQUEST_TIMEOUT_MS="15000"
export TFC_TOKEN="your-terraform-cloud-token"

# Run the server
npm start

Testing

See the TESTS.md file for information about testing this project.

Installation

TypingMind
Prerequisites:

Node.js 18+

{
  "mcpServers": {
    "terraform-registry": {
      "command": "npx",
      "args": [
        "-y",
        "terraform-mcp-server"
      ]
    }
  }
}

Available Tools

  • providerDetails

    Get detailed information about a Terraform provider by name and optionally version.

  • resourceUsage

    Get an example usage of a Terraform resource and related resources.

  • moduleSearch

    Search for and recommend Terraform modules based on a query.

  • listDataSources

    List all available data sources for a provider and their basic details.

  • resourceArgumentDetails

    Fetches comprehensive details about a specific resource type's arguments, including required and optional attributes, nested blocks, and their descriptions.

  • moduleDetails

    Retrieves detailed metadata for a Terraform module including versions, inputs, outputs, and dependencies.

  • functionDetails

    Get details about a Terraform provider function.

  • providerGuides

    List and view provider-specific guides, including version upgrades and feature guides.

  • policySearch

    Search for policy libraries in the Terraform Registry.

  • policyDetails

    Get detailed information about a specific policy library including its latest version.

Use Terraform Registry MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once Terraform Registry is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. You can run MCP locally on your device or connect to a remote MCP server URL.

Option 1: Use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add Terraform Registry as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the Terraform Registry MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "terraform-registry": {
      "command": "npx",
      "args": [
        "-y",
        "terraform-mcp-server"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the Terraform Registry MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the Terraform Registry MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use Terraform Registry to help me with this task?
Terraform Registry
Sure. I read it.
Here is what I found using Terraform Registry.

Option 2: Add an MCP server URL

Use this when Terraform Registry is already hosted remotely or your team wants one shared connector that multiple users can access.

1

Open MCP connectors

In TypingMind, go to Plugins, open MCP connectors, then choose Add URL.

  1. Open TypingMind in your browser.
  2. Go to Plugins.
  3. Open MCP connectors.
  4. Click Add URL.
TypingMind Add Custom MCP Server URL form
2

Paste the server URL

Enter your server URL in the Server URL field. Add a connection name, description, icon, custom HTTP headers, or OAuth client settings if the server requires them.

  1. Paste your server URL into the Server URL field.
  2. Enter a connection name for Terraform Registry.
  3. Add a description and icon if you want it to be easier to identify.
  4. Add custom HTTP headers or OAuth client details if the server requires authentication.
3

Create the connection

Click Create connection, then return to the Plugins list and confirm the new MCP connection is active.

  1. Click Create connection.
  2. Return to the MCP connectors list.
  3. Confirm the Terraform Registry connection appears as active.
  4. Refresh the plugin list if the connection does not appear immediately.
4

Switch models without reconnecting

Start a chat with your preferred model, enable the Terraform Registry tools from Plugins, and switch to another model whenever needed. The MCP connection stays available to the TypingMind workspace.

  1. Start a new chat in TypingMind.
  2. Select the AI model you want to use.
  3. Enable the Terraform Registry tools from Plugins.
  4. Ask the model to use the tool when needed.
  5. Switch to another AI model and reuse the same MCP connection.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use Terraform Registry to help me with this task?
Terraform Registry
Sure. I read it.
Here is what I found using Terraform Registry.

Frequently asked questions

What is the Terraform Registry MCP server used for?

Terraform Registry is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use Terraform Registry MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use Terraform Registry with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use Terraform Registry MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With Terraform Registry connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect Terraform Registry MCP to TypingMind?

Terraform Registry can be connected in TypingMind with the local MCP connector or by adding a remote MCP server URL. Use the local connector when the server needs access to files, apps, or private resources on your device, and use a server URL when the MCP server is hosted remotely.

What tools does Terraform Registry MCP provide in TypingMind?

Terraform Registry exposes 10 MCP tools that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use Terraform Registry MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If Terraform Registry requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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