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Cursor Cursor ​

Setup Cursor to correctly generate Avo code based on your prompt.

Quick use ​

Paste the docs link in the chat window with your prompt and Cursor's web search will fetch it.

bash
Read https://docs.avohq.io/4.0/docs-map.md and use it as a reference for Avo code.

Custom docs ​

  1. In the chat window type @Docs
  2. Choose Add new doc
  3. Paste this: https://docs.avohq.io/4.0/docs-map.md
  4. Now in chat window you can type @Docs and choose Avo to provide Avo's docs to Cursor.

Project-level permanent setup ​

Cursor reads the AGENTS.md file from your repository. Add a line pointing to Avo's docs:

bash
When working with Avo, use the docs at https://docs.avohq.io/4.0/docs-map.md as a reference.

Or save the docs in your repo and reference the file from AGENTS.md:

bash
curl -L https://docs.avohq.io/4.0/docs-map.md --create-dirs -o docs/avo-docs-map.md

MCP server ​

MCP is an API to communicate with AI models. You can add MCP servers and Cursor will communicate with them to get more accurate results.

I suggest using Context7 MCP server which provides many libraries including Avo's docs.

Add this to .cursor/mcp.json in your project (or ~/.cursor/mcp.json to enable it globally):

json
// .cursor/mcp.json
{
  "mcpServers": {
    "Context7": {
      "command": "npx",
      "args": ["-y", "@upstash/context7-mcp@latest"]
    }
  }
}

Now in Agent Mode you can ask AI anything about Avo, and write use context7 at the end of your prompt.

For example:

bash
create a new Avo resource for a product model. use context7