Web search API for AI agents – cited context in one call

Created by

Perceptron Data

Actor

Research Agent – Evidence-Graded Web Search for RAG

Send a question, get a ready-to-paste context block: Google results and Wikipedia read in full, the passages that answer the question, numbered sources [1], [2] … with URL, date and evidence level. For MCP, LangChain, n8n or your own agent.

Try for free

Research Agent – Evidence-Graded Web Search for RAGperceptr0n/research-agent

query

status

contextTokens

durationSeconds

+1 field

Input

Question:What are the main differences between PostgreSQL and MySQL?

Sources:web+1

Token budget per question:3000

Output fields

query

status

contextTokens

durationSeconds

context

How it works

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The Research Agent – Evidence-Graded Web Search for RAG Actor is ready to run with the inputs already set for "Web search API for AI agents – cited context in one call". Sign up or log in and you'll land in Apify Console with a copy of this exact task.

Start the "Web search API for AI agents – cited context in one call" task

The Research Agent – Evidence-Graded Web Search for RAG Actor will start running based on the input automatically. You can also change all the input fields, like question, sources, and more, to match your specific use case.

Receive the "Web search API for AI agents – cited context in one call" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as query, status, contexttokens, and more.