apify-content-analytics

---

name: apify-content-analytics description: Track engagement metrics, measure campaign ROI, and analyze content performance across Instagram, Facebook, YouTube, and TikTok.

Content Analytics

Track and analyze content performance using Apify Actors to extract engagement metrics from multiple platforms.

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: Identify content analytics type (select Actor)
- [ ] Step 2: Fetch Actor schema via mcpc
- [ ] Step 3: Ask user preferences (format, filename)
- [ ] Step 4: Run the analytics script
- [ ] Step 5: Summarize findings

Step 1: Identify Content Analytics Type

Select the appropriate Actor based on analytics needs:

User Need	Actor ID	Best For
Post engagement metrics	apify/instagram-post-scraper	Post performance
Reel performance	apify/instagram-reel-scraper	Reel analytics
Follower growth tracking	apify/instagram-followers-count-scraper	Growth metrics
Comment engagement	apify/instagram-comment-scraper	Comment analysis
Hashtag performance	apify/instagram-hashtag-scraper	Branded hashtags
Mention tracking	apify/instagram-tagged-scraper	Tag tracking
Comprehensive metrics	apify/instagram-scraper	Full data
API-based analytics	apify/instagram-api-scraper	API access
Facebook post performance	apify/facebook-posts-scraper	Post metrics
Reaction analysis	apify/facebook-likes-scraper	Engagement types
Facebook Reels metrics	apify/facebook-reels-scraper	Reels performance
Ad performance tracking	apify/facebook-ads-scraper	Ad analytics
Facebook comment analysis	apify/facebook-comments-scraper	Comment engagement
Page performance audit	apify/facebook-pages-scraper	Page metrics
YouTube video metrics	streamers/youtube-scraper	Video performance
YouTube Shorts analytics	streamers/youtube-shorts-scraper	Shorts performance
TikTok content metrics	clockworks/tiktok-scraper	TikTok analytics

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., apify/instagram-post-scraper).

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 Findings

After completion, report:

• Number of content pieces analyzed
• File location and name
• Key performance insights
• Suggested next steps (deeper analysis, content optimization)

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