For developers

AI answers as JSON, the way APIs should work

POST a prompt, get the engine's answer — text, markdown, cited sources and engine-specific fields — in a documented schema. Sync when you need it now, async with webhooks when you need it at scale.

Start free Quickstart

Built API-first

One OpenAPI document covering every engine; generate a client in your stack
SDKs for TypeScript/JavaScript and Python, an n8n node, LangChain tools and a hosted MCP server
Async tasks and 500-task batches with idempotency keys; results polled or pushed to a signed webhook
country on every engine: 213 countries on ChatGPT, Gemini, AI Mode and Google Search; city-level on AI Mode and Google Search
Credits priced per request; only successful results are charged

What teams build on it

AI visibility trackers and GEO dashboards, agent tools that need grounded web answers, research datasets across markets, and monitoring pipelines that diff answers over time.

The quickstart covers the first request end to end; the API reference lists every field per engine.

Try it

curl -X POST "https://api.answerline.dev/v1/monitor/chatgpt" \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt":"What are the best observability tools for Kubernetes?","country":"US","include":{"markdown":true,"searchQueries":true}}'

Sync or queue it with POST /v1/async/task. Full field list on the ChatGPT page and in the API reference.