Trustpilot business reviews as clean, structured JSON for reputation monitoring. You send company URLs, you get back every review: star rating, full text, verified status, date of experience, reviewer location, and any reply the business posted, plus the company overall rating and its full star distribution.

This is built for watching a rating over time, not one export and done. The date of experience stays separate from the posting date, replies come through as their own structured entries, and the star breakdown gives you counts and percentages at each level, so you can catch a one-star share creeping up before the headline average moves.

What each review row includes

• Title, full text, star rating, posting date, and the separate date of experience

• Verified-review flag, verified-business flag, useful-vote count, and the reviewer total review count so you can weight who is talking

• The company reply, if there is one, and its date

• Company overall score, its word label (like Excellent), total review count, and the 5-to-1 star split

• Company website, category path, and the contact fields the business publishes itself

• A one-line plain-language summary, so an AI agent can read a record without any parsing

How you run it

Paste one or more company review-page URLs (a bare domain works too), set maxReviewsPerCompany as your cost cap, and optionally limit to a recent window. One JSON row comes back per review, with CSV and Excel export built in. You pay per review returned, and a company that comes back empty costs nothing.

What it does not do

There is no keyword or category search, so you bring the company list. Date filtering is limited to the fixed windows the source offers (last 30 days, 3 months, 6 months, or 12 months), not arbitrary calendar dates.

Example tasks and use cases

• Get Trustpilot Reviews by API from Company URLs - the developer starting point: paste company URLs, get structured review JSON back.

• Monitor Trustpilot Reputation for Any Company - pre-wired for scheduling, so the star breakdown becomes a time series rather than a snapshot.

• Audit Trustpilot Reviews for Fake Review Signals - weight reviews by the verified flag and reviewer history to separate established reviewers from one-time accounts.

• Build a Customer Review Dataset for Sentiment Analysis - flat rows of review text with star ratings attached, ready for a sentiment model.

• Export Trustpilot Reviews to CSV for Any Company - straight to a spreadsheet, no code, for teams that live in Excel or Sheets.

• Read Trustpilot Reviews in Claude via MCP - a working MCP configuration so an agent can pull reviews inside a conversation.

Works with MCP

The Actor runs over the hosted Apify MCP server, so Claude, Cursor, or any MCP client can call it as a tool. Ask something like "summarise the one-star reviews for this company and flag any without a reply" and you get structured rows back, no scraping code.

Related review APIs

• G2 Reviews API - B2B software reviews, the natural pair when buyers research on both G2 and Trustpilot.

• Glassdoor Reviews API - employer reviews, which often explain a customer-facing rating slide.

• Yelp Reviews API - local business reviews, for brands with physical locations.

• OpenTable Reviews API - restaurant reviews and diner sentiment.

Keywords and topics: reputation monitoring, trustpilot api, customer review data, review scraping, brand and competitor monitoring, sentiment analysis, MCP tool for AI agents.