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Documentation Index

Fetch the complete documentation index at: https://docs.rafftechnologies.com/llms.txt

Use this file to discover all available pages before exploring further.

Updated May 8, 2026 Raff’s documentation ships with a built-in MCP server (Model Context Protocol) — a standardized way for AI assistants to read your docs as a tool. Connect Claude, Cursor, or any MCP-compatible client to one URL and the AI gets live, up-to-date Raff knowledge: it can search the docs, pull specific pages, and cite real content when answering your questions about Raff.

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Endpoint

https://docs.rafftechnologies.com/mcp
This is the URL you point any MCP client at. It’s a public, read-only server — no API key, no setup on Raff’s side, no rate limit beyond fair-use. The server exposes two tools to your AI:
ToolWhat it returns
Search docsFull-text search across every published page on Raff’s docs site
Query docs filesystemPulls a specific page or section by its docs path (e.g. products/build/virtual-machines/quickstart-guides/create-a-vm)
When you ask your AI a Raff question, the model decides which tool to call, gets the relevant content back, and answers with that content as grounding. No hallucinations about endpoints or features that don’t exist.
Edit Claude Desktop’s MCP config:
  • macOS — ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows — %APPDATA%\Claude\claude_desktop_config.json
Add the Raff docs server:
{
  "mcpServers": {
    "raff-docs": {
      "url": "https://docs.rafftechnologies.com/mcp"
    }
  }
}
Restart Claude Desktop. In any new conversation, Claude can now call raff-docs.search and raff-docs.query automatically when answering Raff questions.

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What changes after you connect

Without MCP, asking Claude or Cursor “How do I attach a Volume to a Raff VM?” gets a generic cloud-VM answer based on the model’s training data — which may be stale, wrong about Raff specifics, or hallucinated. With MCP connected:
  1. You ask the same question
  2. The model calls raff-docs.search("attach volume to VM") → gets back the real attach-to-vm.mdx page from Raff’s docs
  3. It answers using your actual product — correct device names (/dev/vdb), correct steps, correct UI labels, correct dashboard paths
  4. The answer cites the docs page so you can click through
This works for everything in the docs: VMs, Volumes, Object Storage, VPC, Public IPs, Firewall, Team & Projects, the API Reference, the CLI, the Terraform provider, billing, troubleshooting — anything published.

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Example questions to try

Once connected, paste these into your AI chat to see grounded answers:
  • “Show me the curl call to create a Raff VM in the production project.”
  • “What does Raff’s Default Firewall block by default and why?”
  • “How do I move a reserved IP between two Raff VMs without downtime?”
  • “Write a Terraform module for a Raff VM with a 100 GB volume and a reserved IPv4.”
  • “What are Raff’s Standard vs Premium plans, and which should I pick for a Postgres database?”
Each of these triggers the AI to call the MCP server, retrieve the relevant docs sections, and answer with real Raff specifics.

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What the MCP server is not

A few things to set expectations:
  • Not an execution endpoint. The MCP server exposes Raff’s docs, not Raff’s API. It cannot create VMs, charge your account, or change anything in your account. To execute actions, your AI tool calls the public REST API directly using your API key.
  • Not authenticated. Anyone with the URL can read the docs through it — exactly what’s true of the public docs site itself. There’s no customer-specific data behind the endpoint.
  • Not a substitute for the API. Use MCP for answering questions about Raff; use the REST API (or raff-go / raff-cli / Terraform) for doing things in Raff.

API Reference

Use the REST API directly — what the AI calls when it needs to do something, not just read about it.

CLI Reference

raff — the command-line equivalent of every Raff API operation.

Terraform Reference

Provision Raff resources declaratively from your AI-generated Terraform.

Quickstart

First Raff API call in under five minutes.
Last modified on May 8, 2026