Web Data for AI Agents
Give an agent a reliable way to fetch structured web data at run time — every Actor is callable over a documented HTTP API, takes a schema-validated input and returns a schema-defined dataset.
How it works
These Actors are designed to chain — the output of one is the input of the next.
- 1
Pick the Actor as a tool
Each Actor’s input schema doubles as a tool definition: named parameters, types and required flags are already declared.
- 2
Call it synchronously
The run-sync-get-dataset-items endpoint runs the Actor and returns results in one request, which suits an agent tool call.
- 3
Consume typed output
The dataset schema tells the agent what fields to expect, so parsing is deterministic rather than guessed from prose.
Scrapers for this use case
5 Goldmine Actors serve this workflow.
Extract Emails, Socials and Contacts from Any Website
Extract email addresses, social media links, and phone numbers from websites, including JavaScript-rendered pages, with support for multiple links and concurrency. Finds contact information from main pages and dedicated contact/about pages.
Scrape LinkedIn Company Details
Scrape detailed LinkedIn company data including employees, about info, stock data, affiliated and similar companies
Google Maps Contact & Social Media Extractor
Extracts business contact information from Google Maps including emails, social media profiles, phone numbers, and more. Perfect for lead generation and market research.
Amazon Product Scraper
Scrapes detailed product information from Amazon product pages including price, features, images, and more
Instagram Profile Scraper
Scrape detailed Instagram user profile information including contact details, social links, and business information
What this does not solve
Worth knowing before you build a process on top of it.
- Runs are asynchronous work with real latency. Synchronous calls are suitable for small inputs, not for large crawls inside a single agent turn.
- Goldmine does not currently publish a hosted MCP server. Actors are reached over the Apify API, and Apify’s own MCP integration is the route for MCP-aware clients.
- Costs scale with results, so an agent given an unbounded input can spend real money — bound it with `maxItems`.