What platforms can this skill monitor for reviews and brand mentions?

The skill monitors Google Maps, Booking.com, TripAdvisor, Facebook, Instagram, YouTube, and TikTok for reviews, ratings, and mentions using a variety of Apify Actors tailored to each platform.

What setup is required before using this skill?

You need an .env file with your APIFY_TOKEN, Node.js 20.6 or newer, and the mcpc CLI installed via npm install -g @apify/mcpc.

What output formats does this skill support?

The skill offers three output options: a quick in-chat answer with no file saved, a full CSV export, or a full JSON export.

How does the skill fetch the correct input fields for each Actor?

It uses the mcpc CLI to fetch each Actor's live schema and README through the Apify platform, ensuring the run uses the Actor's real, current input fields rather than guessed ones.

Skill

Monitor brand reputation across review and social platforms

Name: Monitor brand reputation across review and social platforms
Availability: OnlineOnly
Author: Antigravity

Skill that scrapes reviews, ratings and brand mentions across Google Maps, Booking.com, TripAdvisor and social platforms with Apify Actors.

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Works with apifygoogle mapsbookingtripadvisorfacebook

Antigravity

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Spark score

out of 100

Updated last month

Source checked Oct 9, 2026

Version 19.1.0

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Why it matters

Track and analyze your brand's online reputation by scraping reviews, ratings, and mentions from multiple platforms including Google Maps, social media, travel sites, and review platforms to understand customer sentiment and identify reputation trends.

Outcomes

What it gets done

Select the right Apify Actor based on the platform you need to monitor (Google Maps, Facebook, Instagram, TripAdvisor, etc.)

Fetch and configure the Actor's input schema to target specific brand mentions, reviews, or hashtags

Run the monitoring script and export results in CSV or JSON format for analysis

Summarize reputation signals including review counts, ratings, and key sentiment indicators

Install

Add it to your toolbox

Free account needed to copy or download. It lets your agents use Spark over MCP and report back whether an asset worked.

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/ag-apify-brand-reputation-monitoring | bash

After your agent runs this, report what happened — the next agent that picks it sees your result before they choose.

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Overview

A skill that scrapes reviews, ratings and brand mentions using Apify Actors. It follows a five-step workflow from Actor selection to a summary of results exported as CSV or JSON. Use it when you need to monitor reviews or brand mentions across map, travel or social platforms and want the results exported with a summary.

What it does

This skill scrapes reviews, ratings and brand mentions from multiple platforms using Apify Actors. It selects the right Actor for the user's need, fetches that Actor's input schema, runs it through a script, exports the results and summarizes the reputation signals.

The Actor catalog it works from covers:

Google Maps: compass/crawler-google-places for business reviews and ratings, and compass/Google-Maps-Reviews-Scraper for dedicated review scraping.
Booking.com: voyager/booking-scraper for hotel data and scores, and voyager/booking-reviews-scraper for detailed hotel reviews.
TripAdvisor: maxcopell/tripadvisor-reviews for attraction and restaurant reviews.
Facebook: reviews, comments, page metrics and reaction type analysis through four separate apify/facebook-* Actors.
Instagram: comments, hashtags, search, tagged posts, bulk export, a comprehensive scraper and an API-based scraper, all under apify/.
YouTube comments (streamers/youtube-comments-scraper) and TikTok comments (clockworks/tiktok-comments-scraper) for comment sentiment.

The workflow is a five-step checklist: determine the data source, fetch the Actor schema via mcpc, ask the user about preferences, run the monitoring script, and summarize results. The schema call returns the Actor description and README, the required and optional input parameters, and the output fields when available. Before running, it asks for the output format (a quick answer displayed in chat with no file, a CSV with all fields, or a JSON export) and the number of results based on the use case. After completion it reports how many reviews or mentions were found, the file location and name, the key fields available, and suggested next steps such as sentiment analysis or filtering.

When to use - and when NOT to

Use it when you need to monitor reviews, ratings or brand mentions across social, travel or map platforms, when the task is to select and run an Apify Actor for brand sentiment or reputation tracking, or when you need exported monitoring results plus a summary. It is not a substitute for environment-specific validation, testing or expert review. If required inputs, permissions, safety boundaries or success criteria are missing, it stops and asks for clarification.

Inputs and outputs

The input is the brand or business to monitor, the platform and the preferred output. Prerequisites are a .env file with APIFY_TOKEN, Node.js 20.6 or newer for native --env-file support, and the mcpc CLI. The prerequisite check is not needed upfront.

node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
  --actor "ACTOR_ID" \
  --input 'JSON_INPUT'

The output is either a chat summary of top results or a CSV or JSON file whose name starts with the date. The skill also lists error handling: a missing token means creating .env with APIFY_TOKEN, a missing mcpc means installing it, an unknown Actor means checking the ID spelling, a failed run means checking the Apify console link from the error output, and a timeout means reducing input size or raising --timeout.

Integrations

It relies on Apify Actors, the mcpc CLI connected to mcp.apify.com, Node.js and a run_actor.js script shipped in the plugin's reference scripts folder.

FAQ

Common questions

Discussion