apify-lead-generation▌
apify/agent-skills · updated Apr 8, 2026
MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.
Multi-platform lead scraping from Google Maps, social media, websites, and search engines.
- ›Supports 16+ Actors covering Google Maps, Instagram, TikTok, Facebook, YouTube, LinkedIn, Google Search, and contact enrichment
- ›Dynamically fetches Actor schemas via mcpc CLI to determine required and optional input parameters before execution
- ›Outputs results as quick chat summaries, CSV, or JSON files with configurable result limits
- ›Requires APIFY_TOKEN in .env file and Node.js 20.6+ for en
Lead Generation
Scrape leads from multiple platforms using Apify Actors.
Prerequisites
(No need to check it upfront)
.envfile withAPIFY_TOKEN- Node.js 20.6+ (for native
--env-filesupport) mcpcCLI tool:npm install -g @apify/mcpc
Workflow
Copy this checklist and track progress:
Task Progress:
- [ ] Step 1: Determine lead source (select Actor)
- [ ] Step 2: Fetch Actor schema via mcpc
- [ ] Step 3: Ask user preferences (format, filename)
- [ ] Step 4: Run the lead finder script
- [ ] Step 5: Summarize results
Step 1: Determine Lead Source
Select the appropriate Actor based on user needs:
| User Need | Actor ID | Best For |
|---|---|---|
| Local businesses | compass/crawler-google-places |
Restaurants, gyms, shops |
| Contact enrichment | vdrmota/contact-info-scraper |
Emails, phones from URLs |
| Instagram profiles | apify/instagram-profile-scraper |
Influencer discovery |
| Instagram posts/comments | apify/instagram-scraper |
Posts, comments, hashtags, places |
| Instagram search | apify/instagram-search-scraper |
Places, users, hashtags discovery |
| TikTok videos/hashtags | clockworks/tiktok-scraper |
Comprehensive TikTok data extraction |
| TikTok hashtags/profiles | clockworks/free-tiktok-scraper |
Free TikTok data extractor |
| TikTok user search | clockworks/tiktok-user-search-scraper |
Find users by keywords |
| TikTok profiles | clockworks/tiktok-profile-scraper |
Creator outreach |
| TikTok followers/following | clockworks/tiktok-followers-scraper |
Audience analysis, segmentation |
| Facebook pages | apify/facebook-pages-scraper |
Business contacts |
| Facebook page contacts | apify/facebook-page-contact-information |
Extract emails, phones, addresses |
| Facebook groups | apify/facebook-groups-scraper |
Buying intent signals |
| Facebook events | apify/facebook-events-scraper |
Event networking, partnerships |
| Google Search | apify/google-search-scraper |
Broad lead discovery |
| YouTube channels | streamers/youtube-scraper |
Creator partnerships |
| Google Maps emails | poidata/google-maps-email-extractor |
Direct email extraction |
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 leads found
- File location and name
- Key fields available
- Suggested next steps (filtering, enrichment)
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
How to use apify-lead-generation on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add apify-lead-generation
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches apify-lead-generation from GitHub repository apify/agent-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate apify-lead-generation. Access the skill through slash commands (e.g., /apify-lead-generation) or your agent's skill management interface.
Security & Verification Notice
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 development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ 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.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★53 reviews- ★★★★★Li Lopez· Dec 28, 2024
Registry listing for apify-lead-generation matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Isabella Menon· Dec 24, 2024
Useful defaults in apify-lead-generation — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Shikha Mishra· Dec 16, 2024
apify-lead-generation fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Aanya Brown· Dec 12, 2024
I recommend apify-lead-generation for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Daniel Thomas· Nov 27, 2024
apify-lead-generation has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Diya Kapoor· Nov 19, 2024
Useful defaults in apify-lead-generation — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Maya Robinson· Nov 15, 2024
Registry listing for apify-lead-generation matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Yash Thakker· Nov 7, 2024
apify-lead-generation is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Diya Jain· Nov 3, 2024
apify-lead-generation reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Dhruvi Jain· Oct 26, 2024
Keeps context tight: apify-lead-generation is the kind of skill you can hand to a new teammate without a long onboarding doc.
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