A Model Context Protocol (MCP) server for accessing the OpenTofu Registry. This server allows language model assistants to search for and retrieve information about OpenTofu providers, modules…
opentofu-mcp-server is an MCP project maintained in the opentofu/opentofu-mcp-server repository. The maintainer describes its purpose as “A Model Context Protocol (MCP) server for accessing the OpenTofu Registry. This server allows language model assistants to search for and retrieve information about OpenTofu…”. Read the project documentation for the complete scope.
The maintainer’s configuration uses https://mcp.opentofu.org/mcp. Check the project’s account and authentication instructions when adding the endpoint to your client.
Project documentation · Repository · Discovery listing. This profile records the public documentation checked on 2026-10-08.
Check the linked publisher documentation and your connected client's tool list. Names and availability can vary with the server version and account permissions.
| Tool | What it does |
|---|---|
| search-opentofu-registry | Search for providers, modules, resources, and data sources |
| get-provider-details | Get detailed information about a specific provider |
| get-module-details | Get detailed information about a specific module |
| get-resource-docs | Get documentation for a specific resource |
| get-datasource-docs | Get documentation for a specific data source |
{
"mcpServers": {
"opentofu": {
"transport": "streamable-http",
"url": "https://mcp.opentofu.org/mcp"
}
}
}From the project documentation. Replace placeholders and example paths before connecting.
The original Chromium automation reference server — simple, screenshot-driven browser control.
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Automates browsers and APIs, enabling Large Language Models (LLMs) to interact with web pages for tasks like screenshot capture and JavaScript
Workers, KV, R2 and D1 by conversation — Cloudflare's official remote servers for building and observability.
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.
Answers, not links — delegate questions to Perplexity's search-grounded models and get cited responses back.