What Is Monocrawl and What Does It Do?

Monocrawl is a social media scraping API that returns public data from 70+ platforms through one key and one unified schema. It is built for developers and AI agents that need profiles, posts, comments, reviews, or price data without writing a separate integration for every platform. You can start with 150 free credits, and failed calls are not charged.

What Monocrawl actually provides

The core product is a single REST and MCP API. Instead of learning TikTok's field names, then Instagram's, then Reddit's, you call one endpoint and get a consistent envelope back.

• One API, one schema — shared fields where platforms match (for example handle, verified, followers), with platform-specific data kept intact rather than flattened away.
• 70+ platforms — including TikTok, Instagram, YouTube, LinkedIn, Facebook, X, Reddit, Google Search, Amazon, eBay, Walmart, Etsy, Airbnb, Booking.com, TripAdvisor, GitHub, Spotify, App Store, Google Play, and Trustpilot.
• 650+ endpoints across REST and MCP.
• Data types — profiles, posts, comments, reviews, and prices.
• MCP support — connect an agent once and it can discover endpoints and pull the public-web data it needs.

The site reports a 2.1s median response time in its own benchmark, zero credits charged for failed calls, and zero credits for cached repeats.

Who it is for

Monocrawl targets two groups:

1. Developers building integrations, dashboards, or data pipelines who want to avoid maintaining dozens of scrapers.
2. AI agents and agent builders who need a stable, discoverable data source rather than brittle per-site scraping.

If you only need one platform and already have a working scraper, the value is lower. The benefit scales with how many platforms and how much schema-normalization work you would otherwise do yourself.

Common use cases

The site lists several concrete applications:

A price-tracking use case is also documented, which fits the price and product data coverage.

How the unified schema works in practice

The clearest way to understand the product is the before/after the site shows. Without Monocrawl, the same profile request returns different shapes per platform:

TikTok /profile
{ "unique_id": "northwind", "verified": true,
  "follower_count": 84200, "video_count": 312 }

Instagram /profile
{ "username": "northwind", "is_verified": true,
  "edge_followed_by": { "count": 1260000 }, "posts_count": 1480 }

With Monocrawl, one call returns normalized fields plus the original platform data:

Monocrawl /profile
handle      northwind
verified    true
followers   84,200
video_count 312          ← platform-specific, kept as returned
platform    tiktok
credits_used 1
cached      false

So your integration code becomes a single destructure — const { handle, verified, followers } = response.data; — instead of a per-platform mapping layer.

Pricing and access

The site references monthly plans, optional subscriber top-ups, and credit packs on its pricing page. It states 150 free credits to start, $0 for failed calls, and zero credits for cached repeats. Specific plan prices are not stated in the available material, so check the pricing page for current numbers before committing.

What to check before adopting

• Platform coverage for your specific target — confirm your platform is in the 70+ list, since the exact set matters more than the count.
• Endpoint availability — 650+ endpoints sounds broad, but verify the specific data type you need (for example, comments on a given platform) exists.
• Credit consumption per call — the example shows credits_used: 1 for a profile call, but cost likely varies by endpoint. Confirm this against your expected volume.
• MCP fit — if you are building an agent, test the MCP connection path first, since that is the primary agent workflow.

If your work involves pulling public data from many platforms into one pipeline, Monocrawl is designed to remove the per-platform integration work. If you need a single source or already have reliable scrapers, the case is weaker.