Multi-platform trend discovery and tracking across Google Trends, Instagram, Facebook, YouTube, and TikTok.
Works with
Supports 19 specialized Apify Actors covering search trends, hashtag tracking, engagement metrics, and viral content discovery across five major platforms
Dynamically fetches Actor schemas using mcpc CLI to retrieve input parameters and output fields before execution
Outputs results in three formats: quick chat display, CSV export, or JSON export with customizable result counts
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionapify-trend-analysisExecute the skills CLI command in your project's root directory to begin installation:
Fetches apify-trend-analysis from apify/agent-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate apify-trend-analysis. Access via /apify-trend-analysis in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Discover and track emerging trends using Apify Actors to extract data from multiple platforms.
(No need to check it upfront)
.env file with APIFY_TOKEN--env-file support)mcpc CLI tool: npm install -g @apify/mcpcCopy this checklist and track progress:
Task Progress:
- [ ] Step 1: Identify trend type (select Actor)
- [ ] Step 2: Fetch Actor schema via mcpc
- [ ] Step 3: Ask user preferences (format, filename)
- [ ] Step 4: Run the analysis script
- [ ] Step 5: Summarize findings
Select the appropriate Actor based on research needs:
| User Need | Actor ID | Best For |
|---|---|---|
| Search trends | apify/google-trends-scraper |
Google Trends data |
| Hashtag tracking | apify/instagram-hashtag-scraper |
Hashtag content |
| Hashtag metrics | apify/instagram-hashtag-stats |
Performance stats |
| Visual trends | apify/instagram-post-scraper |
Post analysis |
| Trending discovery | apify/instagram-search-scraper |
Search trends |
| Comprehensive tracking | apify/instagram-scraper |
Full data |
| API-based trends | apify/instagram-api-scraper |
API access |
| Engagement trends | apify/export-instagram-comments-posts |
Comment tracking |
| Product trends | apify/facebook-marketplace-scraper |
Marketplace data |
| Visual analysis | apify/facebook-photos-scraper |
Photo trends |
| Community trends | apify/facebook-groups-scraper |
Group monitoring |
| YouTube Shorts | streamers/youtube-shorts-scraper |
Short-form trends |
| YouTube hashtags | streamers/youtube-video-scraper-by-hashtag |
Hashtag videos |
| TikTok hashtags | clockworks/tiktok-hashtag-scraper |
Hashtag content |
| Trending sounds | clockworks/tiktok-sound-scraper |
Audio trends |
| TikTok ads | clockworks/tiktok-ads-scraper |
Ad trends |
| Discover page | clockworks/tiktok-discover-scraper |
Discover trends |
| Explore trends | clockworks/tiktok-explore-scraper |
Explore content |
| Trending content | clockworks/tiktok-trends-scraper |
Viral content |
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/google-trends-scraper).
This returns:
Before running, ask:
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
After completion, report:
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
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
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I recommend apify-trend-analysis for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Keeps context tight: apify-trend-analysis is the kind of skill you can hand to a new teammate without a long onboarding doc.
Solid pick for teams standardizing on skills: apify-trend-analysis is focused, and the summary matches what you get after install.
We added apify-trend-analysis from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
apify-trend-analysis fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
apify-trend-analysis has been reliable in day-to-day use. Documentation quality is above average for community skills.
Keeps context tight: apify-trend-analysis is the kind of skill you can hand to a new teammate without a long onboarding doc.
apify-trend-analysis is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Solid pick for teams standardizing on skills: apify-trend-analysis is focused, and the summary matches what you get after install.
We added apify-trend-analysis from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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