anysite Influencer Discovery

Find and analyze influencers across social platforms using anysite MCP. Discover content creators, evaluate their reach and engagement, and identify partnership opportunities.

Overview

Discover influencers across Instagram, Twitter, LinkedIn, YouTube
Analyze engagement and audience quality
Track activity and content patterns
Evaluate partnership fit based on niche and metrics
Build influencer lists with contact information

Coverage: 85% - Excellent for Instagram, Twitter, LinkedIn, YouTube influencers.

v2 Tool Interface

All data fetching uses the anysite v2 meta-tools:

execute(source, category, endpoint, params) - Fetch data. Returns first page + cache_key.
get_page(cache_key, offset, limit) - Load more items from a previous execute (when next_offset is returned).
query_cache(cache_key, conditions, sort_by, aggregate, group_by) - Filter, sort, or aggregate cached data without new API calls.
export_data(cache_key, format) - Export full dataset as CSV, JSON, or JSONL. Returns a download URL.

Error handling: Check responses for llm_hint fields that provide actionable guidance on failures (e.g., alias not found, URN required).

Supported Platforms

✅ Instagram: Profile stats, posts, followers, engagement, Reels
✅ Twitter/X: User search, followers, tweets, engagement
✅ LinkedIn: B2B influencers, thought leaders, professional content
✅ YouTube: Channel search, subscribers, views, video performance
✅ Reddit: Community influencers, karma, post quality

Quick Start

Step 1: Search for Influencers

By platform:

Instagram: execute("instagram", "search", "search_posts", {"query": "niche keywords", "count": 50}) with niche keywords + hashtags
Twitter: execute("twitter", "search", "search_users", {"query": "niche keywords", "count": 50}) with niche keywords
LinkedIn: execute("linkedin", "search", "search_users", {"keywords": "industry thought leader", "count": 50}) with industry + "thought leader"
YouTube: execute("youtube", "search", "search_videos", {"query": "niche", "count": 50}) with niche, then analyze channels

Step 2: Analyze Profiles

Get detailed metrics:

Instagram: execute("instagram", "user", "user", {"user": "username"}) -> followers, posts, engagement rate
Twitter: execute("twitter", "user", "get", {"username": "handle"}) -> followers, tweet frequency
YouTube: execute("youtube", "channel", "channel_videos", {"channel": "...", "count": 30}) -> subscribers, views, growth
LinkedIn: execute("linkedin", "user", "user", {"user": "alias"}) -> connections, post engagement

Step 3: Evaluate Engagement

Check engagement quality:

Post likes, comments, shares
Engagement rate (engagement / followers)
Audience authenticity (comment quality)
Content consistency (posts per week)

Use query_cache(cache_key, sort_by=[{"field": "like_count", "order": "desc"}]) to rank posts by engagement without re-fetching.

Step 4: Build Influencer List

Export with export_data(cache_key, "csv"):

Name, handle, platform
Follower count, engagement rate
Niche/topics, content type
Contact info (if available)
Partnership fit score

Common Workflows

Workflow 1: Instagram Influencer Discovery

Scenario: Find Instagram influencers in sustainable fashion (10k-100k followers)

Steps:

Search by Hashtag/Keywords

execute("instagram", "search", "search_posts", {
  "query": "sustainable fashion OR eco friendly fashion",
  "count": 100
})
-> Extract unique user handles from results
-> Use get_page(cache_key, offset, 50) if next_offset returned for more results

Analyze Each Creator

For each unique handle:
  execute("instagram", "user", "user", {"user": "username"})
  -> Follower count, bio, profile type

Filter for:
- 10k-100k followers
- Business/Creator account
- Bio mentioning sustainability

Evaluate Content

For qualified creators:
  execute("instagram", "user", "user_posts", {"user": "username", "count": 30})

Analyze:
- Post frequency (consistency)
- Engagement rate per post
- Content quality and style
- Brand partnerships visible

Use query_cache(cache_key, sort_by=[{"field": "like_count", "order": "desc"}]) to find top posts
Use query_cache(cache_key, aggregate=[{"field": "like_count", "function": "avg"}]) for average engagement

Check Audience Quality

execute("instagram", "post", "post_likes", {"post": "post_id", "count": 100})
execute("instagram", "post", "post_comments", {"post": "post_id", "count": 50})

Look for:
- Real comments (not just emojis)
- Engaged community (questions, discussions)
- Geographic relevance

Get Contact Information

From Instagram bio:
- Email addresses
- Website links

If LinkedIn mentioned:
  execute("linkedin", "search", "search_users", {"keywords": "first_name last_name"})
  execute("linkedin", "user", "user", {"user": "alias_from_search"})

Expected Output:

20-40 qualified influencers
Engagement metrics for each
Contact information for 60-70%
Partnership fit scores

Use export_data(cache_key, "csv") to generate a downloadable influencer list.

Workflow 2: LinkedIn Thought Leader Identification

Scenario: Find B2B thought leaders in SaaS/sales

Steps:

Search for Active Posters

execute("linkedin", "search", "search_users", {
  "keywords": "SaaS sales thought leader",
  "title": "VP Sales OR Head of Sales OR Chief Revenue Officer",
  "count": 100
})

Analyze Post Activity

For each candidate:
  execute("linkedin", "post", "get_user_posts", {"user": "urn", "count": 50})

Filter for:
- Posts 2-3x per week minimum
- High engagement (100+ reactions)
- Original content (not just shares)

Use query_cache(cache_key, conditions=[{"field": "comment_count", "operator": ">", "value": 10}])
to filter for high-engagement posts

Evaluate Influence

Check post engagement:
- Average reactions per post
- Comment quality and quantity
- Share count
- Follower growth signals

Use query_cache(cache_key, aggregate=[
  {"field": "comment_count", "function": "avg"},
  {"field": "share_count", "function": "avg"}
]) for average metrics

Assess Content Quality

Review posts for:
- Expertise demonstration
- Original insights
- Engagement with comments
- Consistency of messaging

Expected Output:

15-25 active thought leaders
Content themes and topics
Engagement metrics
Partnership opportunities (guest posts, quotes, etc.)

Use export_data(cache_key, "csv") to export the thought leader list.

Workflow 3: YouTube Creator Research

Scenario: Find YouTube creators in tech reviews

Steps:

Search for Niche Content

execute("youtube", "search", "search_videos", {
  "query": "tech review 2026",
  "count": 100
})
-> Extract unique channel names
-> Use get_page(cache_key, offset, 50) if more results needed

Analyze Channels

For each channel:
  execute("youtube", "channel", "channel_videos", {"channel": "channel_id", "count": 30})

Check:
- Subscriber count
- Upload frequency
- Average views per video
- Video length (long-form vs shorts)

Use query_cache(cache_key, aggregate=[{"field": "view_count", "function": "avg"}]) for average views

Evaluate Video Performance

For top videos:
  execute("youtube", "video", "video", {"video": "video_id"})

Metrics:
- View count
- Like/dislike ratio
- Comments count
- Watch time signals (retention)

Analyze Audience Engagement

execute("youtube", "video", "video_comments", {"video": "video_id", "count": 100})

Look for:
- Active community
- Technical discussions
- Purchase decisions influenced

Expected Output:

10-20 relevant channels
Subscriber and view metrics
Engagement analysis
Partnership fit assessment

Use export_data(cache_key, "csv") to export channel data.

MCP Tools Reference (v2)

Instagram

execute("instagram", "search", "search_posts", {"query": ..., "count": N}) - Find posts by keywords/hashtags
execute("instagram", "user", "user", {"user": ...}) - Get profile with followers, bio
execute("instagram", "user", "user_posts", {"user": ..., "count": N}) - Get recent posts with engagement
execute("instagram", "post", "post_likes", {"post": ..., "count": N}) - Check audience authenticity
execute("instagram", "post", "post_comments", {"post": ..., "count": N}) - Analyze engagement quality
execute("instagram", "user", "user_friendships", {"user": ..., "count": N, "type": "followers"}) - Get followers list (for analysis)

Twitter/X

execute("twitter", "search", "search_users", {"query": ..., "count": N}) - Find users by keywords/bio
execute("twitter", "user", "get", {"username": ...}) - Get profile with followers, tweets
execute("twitter", "user_tweets", "get", {"username": ...}) - Get recent tweets with engagement
execute("twitter", "search", "search_posts", {"query": ..., "count": N}) - Find influential tweets in niche

execute("linkedin", "search", "search_users", {"keywords": ..., "count": N}) - Find professionals by keywords/title
execute("linkedin", "user", "user", {"user": ...}) - Get complete profile (includes skills with with_skills: true)
execute("linkedin", "post", "get_user_posts", {"user": "urn", "count": N}) - Get post history and engagement
execute("linkedin", "user", "user_skills", {"urn": ..., "count": N}) - Verify expertise (requires URN from profile)

Note: LinkedIn connection count is returned in the profile response (connection_count field). No separate endpoint needed.

YouTube

execute("youtube", "search", "search_videos", {"query": ..., "count": N}) - Find videos by keywords
execute("youtube", "channel", "channel_videos", {"channel": ..., "count": N}) - Get all videos from channel
execute("youtube", "video", "video", {"video": ...}) - Get video metrics (views, likes)
execute("youtube", "video", "video_comments", {"video": ..., "count": N}) - Analyze audience engagement

execute("reddit", "search", "search_posts", {"query": ..., "count": N}) - Find influential posts in subreddits
execute("reddit", "user", "user_posts", {"username": ..., "count": N}) - Get user's post history
execute("reddit", "user", "user_comments", {"username": ..., "count": N}) - Analyze community engagement

Web Scraping

execute("webparser", "parse", "parse", {"url": ...}) - Scrape any webpage for contact info, media kits, etc.

Pagination, Caching & Export

get_page(cache_key, offset, limit) - Fetch additional pages from any execute() result
query_cache(cache_key, conditions, sort_by, aggregate, group_by) - Filter/sort/aggregate cached data
export_data(cache_key, "csv"|"json"|"jsonl") - Export full dataset as downloadable file

Output Formats

Chat Summary:

Top 10 influencers with key metrics
Engagement rate comparison
Partnership recommendations
Contact information found

CSV Export (via export_data(cache_key, "csv")):

Influencer name, handle, platform
Followers, engagement rate
Niche, content type
Email, website
Fit score (1-100)

JSON Export (via export_data(cache_key, "json")):

Complete profile data
All posts with engagement
Audience demographics (if available)
Historical metrics

Influencer Evaluation Framework

Reach Metrics

Followers: Total audience size
Views: Average content views
Growth: Follower growth rate

Engagement Metrics

Rate: Engagement / Followers
Quality: Comment depth and relevance
Consistency: Regular engagement patterns

Authenticity Indicators

Audience Quality: Real vs. fake followers
Comment Quality: Meaningful discussions
Growth Pattern: Organic vs. purchased
Engagement Distribution: Consistent vs. spiky

Content Quality

Production Value: Visual/audio quality
Originality: Unique vs. repurposed
Consistency: Regular posting schedule
Niche Alignment: On-brand content

Partnership Fit

Audience Overlap: Match with target market
Brand Alignment: Values and messaging
Professionalism: Past partnerships, disclosure
Availability: Contact information, responsiveness

Advanced Features

Micro-Influencer Strategy

Focus on 10k-50k followers for higher engagement:

Benefits:
- Higher engagement rates (5-10% vs. 1-3%)
- More authentic audience connections
- Lower partnership costs
- Niche expertise

Discovery approach:
- Use hashtag searches via execute("instagram", "search", "search_posts", ...)
- Use query_cache() to filter by engagement rate vs. reach
- Prioritize niche relevance over size

Multi-Platform Presence Analysis

Identify influencers active across platforms:

1. Find on Instagram/Twitter
2. Search LinkedIn for professional presence:
   execute("linkedin", "search", "search_users", {"keywords": "name"})
3. Check for YouTube channel:
   execute("youtube", "search", "search_videos", {"query": "creator name", "count": 10})
4. Look for website/blog:
   execute("webparser", "parse", "parse", {"url": "website_url"})

Benefits:
- Multiple touchpoints
- Diverse content formats
- Professional credibility
- Larger total reach

Audience Demographics Research

Analyze who follows the influencer:

Instagram:
- execute("instagram", "user", "user_friendships", {"user": "username", "count": 100, "type": "followers"})
- Analyze follower profiles for patterns
- Use query_cache(cache_key, group_by="location") to segment by geography

LinkedIn:
- Check who engages with posts
- Identify follower job titles/industries from post comments

YouTube:
- Analyze comment demographics via execute("youtube", "video", "video_comments", ...)
- Check subscriber locations (if available)

Reference Documentation

DISCOVERY_CRITERIA.md - Influencer evaluation criteria, scoring frameworks, and niche identification strategies

Troubleshooting

No Influencers Found:

Broaden search keywords
Try multiple hashtags
Search across multiple platforms
Reduce minimum follower requirements

Low Engagement Rates:

Use query_cache(cache_key, conditions=[{"field": "engagement_rate", "operator": ">", "value": 0.03}]) to filter
Focus on micro-influencers (smaller = higher engagement)
Check for bot followers (sudden spikes)

No Contact Information:

Check bio for email/website
Look for LinkedIn profile via execute("linkedin", "search", "search_users", {"keywords": "name"})
Try website domain: execute("webparser", "parse", "parse", {"url": "domain"})
Search for media kit or press page

API Errors:

Check llm_hint in error responses for actionable guidance
LinkedIn endpoints requiring URN: get URN from profile response first, do not guess aliases
Use execute("linkedin", "search", "search_users", ...) to find correct aliases before fetching profiles

Ready to discover influencers? Ask Claude to help you find content creators, analyze engagement, or build influencer lists for your marketing campaigns!

anysite-influencer-discovery

anysite Influencer Discovery

Overview

v2 Tool Interface

Supported Platforms

Quick Start

Common Workflows

Workflow 1: Instagram Influencer Discovery

Workflow 2: LinkedIn Thought Leader Identification

Workflow 3: YouTube Creator Research

MCP Tools Reference (v2)

Instagram

Twitter/X

LinkedIn

YouTube

Reddit

Web Scraping

Pagination, Caching & Export

Output Formats

Influencer Evaluation Framework

Reach Metrics

Engagement Metrics

Authenticity Indicators

Content Quality

Partnership Fit

Advanced Features

Micro-Influencer Strategy

Multi-Platform Presence Analysis

Audience Demographics Research

Reference Documentation

Troubleshooting