Build with AnswerLine
Send a prompt and get back, as JSON, the answer ChatGPT, Gemini, Perplexity, Copilot, Grok, Google AI Mode, Google Search, and Google News show a person.
1
Get an API key
Sign up and copy a key from the dashboard. The first 100 requests are free.
2Send a first request
One call, one answer, in curl, TypeScript or Python.
3Go async at scale
Queue batches of up to 500 tasks and get results by webhook.
First request
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 running shoes for flat feet?","country":"US","include":{"markdown":true}}'import { Client } from "@answerline/sdk";
const client = new Client({ apiKey: process.env.API_KEY! });
const answer = await client.monitor.chatgpt({
"prompt": "What are the best running shoes for flat feet?",
"country": "US",
"include": {
"markdown": true
}
});import os
from answerline import Client
with Client(os.environ["API_KEY"]) as client:
answer = client.monitor.chatgpt(
prompt="What are the best running shoes for flat feet?",
country="US",
include={
"markdown": True
},
)
Set API_KEY to your key first. Install an SDK with npm install @answerline/sdk or pip install answerline. The quickstart covers async tasks, webhooks and country targeting.
Use it from your AI assistant
The hosted MCP server turns every engine into a tool your assistant can call.
claude mcp add --transport http answerline https://mcp.answerline.dev/mcp --header "Authorization: Bearer $API_KEY"{
"mcpServers": {
"answerline": {
"url": "https://mcp.answerline.dev/mcp",
"headers": {
"Authorization": "Bearer sk_..."
}
}
}
}https://mcp.answerline.dev/<API_KEY>/mcpEngines
Each engine page lists the fields it returns and its price. Request options are in the API reference.