These example prompts can be used with AI coding assistants (Claude, ChatGPT, Copilot, Cursor, etc.) to quickly build integration apps against the Brivo Eagle Eye Video API. Click "Copy" on any prompt block below and paste it into your assistant.
Before You Start
- Obtain Eagle Eye Networks API credentials (client ID, client secret).
- Point your AI assistant at https://apidocs.brivo.com/llms.txt. It is the entry point to all Brivo API documentation — the AI follows it to find every reference file it needs.
Example Prompts
Camera Lister CLI
A small Node.js CLI that authenticates with the Eagle Eye Video API and
prints the cameras available to your account in a readable table. Requires
EEN_CLIENT_ID and EEN_CLIENT_SECRET in .env.
Copy this prompt into your AI assistant
Create a Node.js CLI that authenticates with the Brivo Eagle Eye Video API and lists the cameras available to my account. Walk the user through the OAuth flow and print camera names and IDs in a readable table. Read https://apidocs.brivo.com/llms.txt for API documentation. Use only llms.txt and the files it references. EEN_CLIENT_ID and EEN_CLIENT_SECRET are in .env. On any API error, print the HTTP status, response body, and the operation that failed.
Live Camera Viewer Web App
A Node.js web application that authenticates with the Eagle Eye Video API
and lets a user search for a camera and view a live feed. Requires
EEN_CLIENT_ID and EEN_CLIENT_SECRET in .env.
Copy this prompt into your AI assistant
Create a Node.js web application that authenticates with the Brivo Eagle Eye Video API and lets a user search for a camera and view a live feed. Read https://apidocs.brivo.com/llms.txt for API documentation. Use only llms.txt and the files it references. EEN_CLIENT_ID and EEN_CLIENT_SECRET are in .env. The browser must not call the Eagle Eye API directly - put the API client behind your Node.js server so the client secret stays server-side. For the live feed, use a player matching the transport the streaming endpoint returns (MJPEG, HLS, or WebRTC). Display API errors in the UI with the HTTP status and response body.
Tips for Better Results
- Always reference llms.txt — Include the full URL
(
https://apidocs.brivo.com/llms.txt) so the AI follows the documented navigation chain to the documentation it needs. - Specify your stack — Framework, language, and bundler so the AI scaffolds the project correctly.
- Proxy from a backend, not the browser — Eagle Eye endpoints are not CORS-friendly and credentials must stay server-side.
- Start focused, then expand — Begin with a single feature (e.g., "list cameras") and iterate. AI assistants produce better code in incremental steps.