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apify-influencer-discovery - Claude MCP Skill

Find and evaluate influencers for brand partnerships, verify authenticity, and track collaboration performance across Instagram, Facebook, YouTube, and TikTok.

SEO Guide: Enhance your AI agent with the apify-influencer-discovery tool. This Model Context Protocol (MCP) server allows Claude Desktop and other LLMs to find and evaluate influencers for brand partnerships, verify authenticity, and track collaboration p... Download and configure this skill to unlock new capabilities for your AI workflow.

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SKILL.md
# Influencer Discovery

Discover and analyze influencers across 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 discovery source (select Actor)
- [ ] Step 2: Fetch Actor schema via mcpc
- [ ] Step 3: Ask user preferences (format, filename)
- [ ] Step 4: Run the discovery script
- [ ] Step 5: Summarize results
```

### Step 1: Determine Discovery Source

Select the appropriate Actor based on user needs:

| User Need | Actor ID | Best For |
|-----------|----------|----------|
| Influencer profiles | `apify/instagram-profile-scraper` | Profile metrics, bio, follower counts |
| Find by hashtag | `apify/instagram-hashtag-scraper` | Discover influencers using specific hashtags |
| Reel engagement | `apify/instagram-reel-scraper` | Analyze reel performance and engagement |
| Discovery by niche | `apify/instagram-search-scraper` | Search for influencers by keyword/niche |
| Brand mentions | `apify/instagram-tagged-scraper` | Track who tags brands/products |
| Comprehensive data | `apify/instagram-scraper` | Full profile, posts, comments analysis |
| API-based discovery | `apify/instagram-api-scraper` | Fast API-based data extraction |
| Engagement analysis | `apify/export-instagram-comments-posts` | Export comments for sentiment analysis |
| Facebook content | `apify/facebook-posts-scraper` | Analyze Facebook post performance |
| Micro-influencers | `apify/facebook-groups-scraper` | Find influencers in niche groups |
| Influential pages | `apify/facebook-search-scraper` | Search for influential pages |
| YouTube creators | `streamers/youtube-channel-scraper` | Channel metrics and subscriber data |
| TikTok influencers | `clockworks/tiktok-scraper` | Comprehensive TikTok data extraction |
| TikTok (free) | `clockworks/free-tiktok-scraper` | Free TikTok data extractor |
| Live streamers | `clockworks/tiktok-live-scraper` | Discover live streaming influencers |

### Step 2: Fetch Actor Schema

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

```bash
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-profile-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):**
```bash
node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
  --actor "ACTOR_ID" \
  --input 'JSON_INPUT'
```

**CSV:**
```bash
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:**
```bash
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 influencers found
- File location and name
- Key metrics available (followers, engagement rate, etc.)
- Suggested next steps (filtering, outreach, deeper analysis)

## 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`

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Information

Repository
arlenagreer/claude_configuration_docs
Author
arlenagreer
Last Sync
5/10/2026
Repo Updated
5/7/2026
Created
4/10/2026

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