Mindcase

What is Mindcase?

Mindcase is an infrastructure layer for extracting web data in a structured, usable format. Instead of building and maintaining your own scrapers, proxies, and parsing pipelines, Mindcase gives you direct access to 75+ live APIs covering popular sources like LinkedIn, Google Maps, and Amazon. Each API returns clean, structured fields—think employee names, titles, locations, or product prices and ratings—so you can plug the data straight into your workflows, databases, or AI agents.

Who it's for

• AI engineers who need reliable, clean web data to feed into agent pipelines without babysitting scraping infrastructure.
• Data teams that require structured datasets from multiple sources—like company employee lists or local business info—without writing custom parsers.
• Product builders who want to spin up a custom API for any specific web source and integrate it in minutes, not weeks.

Key features

75+ ready-made APIs

Mindcase ships with a broad catalog of live APIs across categories like LinkedIn, Google Maps, and Amazon. Each endpoint is purpose-built—for example, LinkedIn Company Employees returns name, title, location, and profile URL per employee, while Google Maps Places delivers ratings, reviews, hours, and contact details. You pick the source, set your parameters, and get structured records back.

Keyless, server-side runs

Every API call runs server-side with no API key management on your end. You configure a run—like entering a company URL and max results—and Mindcase handles the execution, returning records with cost and elapsed time transparently displayed. This removes the usual friction of authentication and IP rotation.

Custom API builder

If a source isn't in the catalog, Mindcase lets you request anything across the web built as a custom API tailored to your use case. This turns one-off scraping needs into repeatable, structured endpoints you can reuse indefinitely.

Agent-ready integration

Mindcase connects directly into AI agent environments—it appears as a connected MCP (Model Context Protocol) server in tools like Claude Code. That means your agents can query live web data mid-task without leaving their native interface, making it a natural fit for autonomous workflows.

What stands out

Mindcase turns the messy web into a clean API layer your agents can query like a database.

The key edge is the combination of breadth and structure. Most scraping tools give you raw HTML or force you to build your own extraction logic. Mindcase flips that: you get pre-parsed, schema-aligned data from 25+ sources out of the box, plus the ability to create custom endpoints for anything missing. The transparent per-record pricing—like 0.4¢ per employee or 0.15¢ per product—also makes cost predictable, which is rare in this space.

Worth checking out if…

You're building AI agents or data pipelines that depend on fresh, structured web data and you'd rather pay per record than maintain scrapers. It's especially compelling if you need multiple sources (LinkedIn, Google Maps, Amazon) under one roof, or if you want to expose a custom web source as a clean API for your team. If you're already using Claude Code or similar MCP-compatible tools, the native connector makes adoption nearly instant.