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name: apify-brand-reputation-monitoring description: "Scrape reviews, ratings, and brand mentions from multiple platforms using Apify Actors." risk: unknown source: community

Brand Reputation Monitoring

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

When to Use

• You need to monitor reviews, ratings, or brand mentions across social, travel, or map platforms.
• The task is to select and run an Apify Actor for brand sentiment or reputation tracking.
• You need exported monitoring results and a summary of reputation signals.

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:

1. 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
2. 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

Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.