Quickstart with AI
Build an Envio HyperIndex indexer end-to-end with an AI coding assistant.
Most developers now reach for an AI coding assistant before they open a file. This guide walks through an AI-centric flow for creating, developing, and deploying a HyperIndex indexer. It is semi-generic, so any capable AI coding assistant (Cursor, Windsurf, Copilot Agent, Continue, etc.) will work. That said, we've seen the best results with Claude Code and recommend starting there.
If you'd rather drive the CLI yourself, see the Quickstart.
Prerequisites
- Node.js (v22 or newer)
- pnpm (recommended but not required)
- Docker Desktop (only needed to run the indexer locally)
- An AI coding assistant (we recommend Claude Code)
Some features below (notably the built-in Claude skills) ship with HyperIndex v3. See the v3 migration guide for current install guidance.
Step 1. Give the Assistant Access to the Envio Docs (MCP)
Envio ships a Model Context Protocol server so your AI assistant can search and read Envio documentation directly instead of guessing from stale training data.
Claude Code:
claude mcp add --transport http envio-docs https://docs.envio.dev/mcp
Cursor / VS Code / other MCP clients, add the endpoint to your MCP config:
{
"mcpServers": {
"envio-docs": {
"url": "https://docs.envio.dev/mcp"
}
}
}
Full setup details in the MCP Server guide. If your assistant doesn't support MCP, you can still point it at the LLM-friendly docs bundle.