Brand Reputation Monitoring

Scrape reviews, ratings, and brand mentions from multiple platforms using Apify Actors.

Prerequisites

(No need to check it upfront)

• .env file with APIFY_TOKEN

• Node.js 20.6+ (for native --env-file support)

• mcpc CLI tool: npm install -g @apify/mcpc

Workflow

Copy this checklist and track progress:

Task Progress:

- [ ] Step 1: Determine data source (select Actor)

- [ ] Step 2: Fetch Actor schema via mcpc

- [ ] Step 3: Ask user preferences (format, filename)

- [ ] Step 4: Run the monitoring script

- [ ] Step 5: Summarize results

Step 1: Determine Data Source

Select the appropriate Actor based on user needs:

User Need

Actor ID

Best For

Google Maps reviews

compass/crawler-google-places

Business reviews, ratings

Google Maps review export

compass/Google-Maps-Reviews-Scraper

Dedicated review scraping

Booking.com hotels

voyager/booking-scraper

Hotel data, scores

Booking.com reviews

voyager/booking-reviews-scraper

Detailed hotel reviews

TripAdvisor reviews

maxcopell/tripadvisor-reviews

Attraction/restaurant reviews

Facebook reviews

apify/facebook-reviews-scraper

Page reviews

Facebook comments

apify/facebook-comments-scraper

Post comment monitoring

Facebook page metrics

apify/facebook-pages-scraper

Page ratings overview

Facebook reactions

apify/facebook-likes-scraper

Reaction type analysis

Instagram comments

apify/instagram-comment-scraper

Comment sentiment

Instagram hashtags

apify/instagram-hashtag-scraper

Brand hashtag monitoring

Instagram search

apify/instagram-search-scraper

Brand mention discovery

Instagram tagged posts

apify/instagram-tagged-scraper

Brand tag tracking

Instagram export

apify/export-instagram-comments-posts

Bulk comment export

Instagram comprehensive

apify/instagram-scraper

Full Instagram monitoring

Instagram API

apify/instagram-api-scraper

API-based monitoring

YouTube comments

streamers/youtube-comments-scraper

Video comment sentiment

TikTok comments

clockworks/tiktok-comments-scraper

TikTok sentiment

Step 2: Fetch Actor Schema

Fetch the Actor's input schema and details dynamically using mcpc:

export $(grep APIFY_TOKEN .env | xargs) && mcpc --json mcp.apify.com --header "Authorization: Bearer $APIFY_TOKEN" tools-call fetch-actor-details actor:="ACTOR_ID" | jq -r ".content"

Replace ACTOR_ID with the selected Actor (e.g., compass/crawler-google-places).

This returns:

• Actor description and README

• Required and optional input parameters

• Output fields (if available)

Step 3: Ask User Preferences

Before running, ask:

• Output format:

• Quick answer - Display top few results in chat (no file saved)

• CSV - Full export with all fields

• JSON - Full export in JSON format

• Number of results: Based on character of use case

Step 4: Run the Script

Quick answer (display in chat, no file):

node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \

  --actor "ACTOR_ID" \

  --input 'JSON_INPUT'

CSV:

node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \

  --actor "ACTOR_ID" \

  --input 'JSON_INPUT' \

  --output YYYY-MM-DD_OUTPUT_FILE.csv \

  --format csv

JSON:

node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \

  --actor "ACTOR_ID" \

  --input 'JSON_INPUT' \

  --output YYYY-MM-DD_OUTPUT_FILE.json \

  --format json

Step 5: Summarize Results

After completion, report:

• Number of reviews/mentions found

• File location and name

• Key fields available

• Suggested next steps (sentiment analysis, filtering)

Error Handling

APIFY_TOKEN not found - Ask user to create .env with APIFY_TOKEN=your_token

mcpc not found - Ask user to install npm install -g @apify/mcpc

Actor not found - Check Actor ID spelling

Run FAILED - Ask user to check Apify console link in error output

Timeout - Reduce input size or increase --timeout