| name | anysite-competitor-intelligence |
| description | Competitive intelligence gathering using anysite MCP server across LinkedIn, social media, Y Combinator, and the web. Track competitor activities, analyze hiring patterns, monitor content strategies, benchmark market positioning, research startup competitors, and gather strategic intelligence. Supports LinkedIn (companies, employees, posts), Instagram, Twitter/X, Reddit, YouTube, Y Combinator, and web scraping. Use when users need to analyze competitors, track competitive movements, research market positioning, monitor hiring velocity, or gather strategic market intelligence. |
anysite Competitor Intelligence
Comprehensive competitive intelligence gathering using anysite MCP server. Track competitors across LinkedIn, social media, and the web to understand their strategies, monitor their activities, and identify competitive opportunities.
Overview
The anysite Competitor Intelligence skill helps you:
- Track competitor companies on LinkedIn and Y Combinator
- Monitor hiring patterns to identify growth areas and strategic priorities
- Analyze content strategies across social platforms
- Benchmark positioning and messaging
- Identify key employees and leadership changes
- Track competitive movements like funding, launches, partnerships
This skill provides 90% coverage of competitive intelligence capabilities with excellent LinkedIn and social media monitoring.
v2 Tool Interface
All data fetching uses the universal execute() meta-tool:
execute(source, category, endpoint, params) → returns data + cache_key
After fetching, use these for analysis and export:
get_page(cache_key, offset, limit) — paginate through large result setsquery_cache(cache_key, conditions, sort_by, aggregate, group_by) — filter/sort/aggregate cached data without re-fetchingexport_data(cache_key, format) — export to CSV, JSON, or JSONL for sharing
Always call discover(source, category) first if unsure about endpoint names or params.
Error handling: Check response for llm_hint field on errors — it provides actionable guidance (e.g., "Likely passed fsd_company URN instead of company: prefix").
Supported Platforms
- LinkedIn (Primary): Company pages, employee search, post monitoring, job listings, growth tracking
- Y Combinator: Startup competitor research, funding data, batch analysis
- Twitter/X: Social presence monitoring, content strategy, engagement analysis
- Reddit: Community sentiment, product discussions, competitor mentions
- Instagram: Brand presence, visual content strategy, influencer partnerships
- YouTube: Video content, channel growth, community engagement
- Web Scraping: Company websites, press releases, blog content
- SEC: Public company filings for competitors
Quick Start
Step 1: Identify Competitors
Choose your competitor identification method:
| Goal | v2 Call | Output |
|---|
| Find similar companies | execute("linkedin", "search", "search_companies", {"keywords": "...", "count": 50}) | Company list with metrics |
| Research startup competitors | execute("yc", "search", "search_companies", {"query": "...", "count": 50}) | YC startups by industry/batch |
| Discover by employee search | execute("linkedin", "search", "search_users", {...}) → extract companies | Companies from employee profiles |
| Find by keywords/industry | execute("linkedin", "search", "search_companies", {"keywords": "...", "industry": "...", "count": 50}) | Filtered company list |
Step 2: Gather Competitive Intelligence
Execute MCP tools to collect competitor data:
Company Profile Analysis
execute("linkedin", "company", "company", {"company": "competitor-name"})
→ Returns: Description, size, location, website, specialties, URN
Employee Intelligence
execute("linkedin", "search", "search_users", {
"company_keywords": "Competitor Inc",
"title": "VP OR Director OR Head",
"count": 50
})
→ Returns: Key employees, org structure insights
→ Use get_page(cache_key, 10, 50) to load more results
Hiring Velocity Analysis
execute("linkedin", "company", "company_employee_stats", {
"urn": {"type": "company", "value": "<company_id>"}
})
→ Returns: Growth metrics, department distribution
→ Use query_cache(cache_key, sort_by=[{"field": "count", "order": "desc"}]) to rank departments
Content Strategy
execute("linkedin", "company", "company_posts", {
"urn": {"type": "company", "value": "<company_id>"},
"count": 20
})
→ Returns: Recent posts, engagement, messaging themes
→ Use query_cache(cache_key, aggregate=[{"field": "reactions", "function": "avg"}]) for engagement stats
Step 3: Process and Analyze
Analyze gathered data for:
- Growth signals: Hiring velocity, funding, expansion
- Strategic priorities: Department hiring, job postings, content themes
- Market positioning: Messaging, target audience, value props
- Competitive threats: New products, partnerships, key hires
Use query_cache() to filter and aggregate without re-fetching:
query_cache(cache_key, conditions=[{"field": "department", "operator": "contains", "value": "Engineering"}])
Step 4: Format Output
Chat Summary: Competitive insights with key findings
CSV Export: export_data(cache_key, "csv") → Competitor comparison matrix
JSON Export: export_data(cache_key, "json") → Complete data for tracking over time
Common Workflows
Workflow 1: Comprehensive Competitor Profile
Scenario: Deep dive on a specific competitor
Steps:
- Company Overview
execute("linkedin", "company", "company", {"company": "competitor"})
→ Size, industry, description, website, founding year
→ Save the URN (convert fsd_company to company: prefix for sub-endpoints)
- Leadership Team
execute("linkedin", "search", "search_users", {
"company_keywords": "Competitor Inc",
"title": "C-level OR VP OR SVP OR President",
"count": 50
})
→ C-suite and VP-level executives
→ Use get_page(cache_key, 10, 50) for more results
- Organizational Structure
execute("linkedin", "company", "company_employee_stats", {
"urn": {"type": "company", "value": "<company_id>"}
})
→ Total employees, growth rate, department breakdown
For each department:
execute("linkedin", "search", "search_users", {
"company_keywords": "Competitor Inc",
"title": "<department_title>",
"count": 50
})
→ Team sizes, key roles
- Hiring Intelligence
execute("linkedin", "search", "search_jobs", {"keywords": "Competitor Inc", "count": 50})
→ Open positions, hiring priorities, expansion areas
→ Use query_cache(cache_key, group_by="location") to see geographic expansion
- Content Strategy
execute("linkedin", "company", "company_posts", {
"urn": {"type": "company", "value": "<company_id>"},
"count": 50
})
→ Posting frequency, themes, engagement levels
execute("twitter", "user", "user", {"user": "competitor"})
execute("twitter", "user", "user_posts", {"user": "competitor", "count": 50})
→ Social media presence and strategy
- Product/Market Intelligence
execute("webparser", "parse", "parse", {"url": "https://competitor.com"})
→ Positioning, messaging, product offerings
execute("webparser", "parse", "parse", {"url": "https://competitor.com/blog"})
→ Content topics, thought leadership
execute("reddit", "search", "search_posts", {"query": "Competitor Inc", "count": 20})
→ Customer sentiment, product feedback
Expected Output:
- Complete company profile
- Leadership team roster (10-20 executives)
- Hiring velocity and priorities
- Content strategy analysis
- Product positioning insights
- Customer sentiment summary
- Use
export_data(cache_key, "csv") to create downloadable competitor report
Workflow 2: Competitive Landscape Mapping
Scenario: Map all competitors in your space
Steps:
- Identify Competitors
execute("linkedin", "search", "search_companies", {
"keywords": "<your industry keywords>",
"industry": "<industry>",
"employee_count": ["51-200", "201-500", "501-1000"],
"count": 50
})
- Filter and Prioritize
For each company:
execute("linkedin", "company", "company", {"company": "<alias>"})
→ Review description for relevance
→ Check employee count and growth
→ Verify competitive overlap
- Categorize Competitors
Direct: Same products, same market
Indirect: Similar products, different market
Potential: Adjacent space, could expand
- Size and Growth Metrics
For each competitor:
execute("linkedin", "company", "company_employee_stats", {
"urn": {"type": "company", "value": "<company_id>"}
})
→ Employee count, growth rate
→ Department distribution
→ Use query_cache() to compare across competitors
- Positioning Analysis
For each competitor:
execute("linkedin", "company", "company_posts", {
"urn": {"type": "company", "value": "<company_id>"},
"count": 10
})
→ Key messaging themes
execute("webparser", "parse", "parse", {"url": "<website>/about"})
→ Value proposition, target market
- Funding and Traction (for startups)
execute("yc", "search", "search_companies", {"query": "<industry>", "count": 50})
→ YC competitors with funding data
→ Use query_cache(cache_key, sort_by=[{"field": "team_size", "order": "desc"}]) to rank by size
For each YC company:
execute("yc", "company", "get", {"slug": "<company_slug>"})
→ Batch, team size, description
Expected Output:
- 20-50 competitors identified
- Categorized by competitive threat level
- Size and growth metrics for each
- Positioning and messaging summaries
- Competitive landscape map
- Use
export_data(cache_key, "csv") for the full comparison matrix
Workflow 3: Hiring Velocity Tracking
Scenario: Monitor competitor hiring to identify growth areas
Steps:
- Baseline Employee Count
execute("linkedin", "company", "company_employee_stats", {
"urn": {"type": "company", "value": "<company_id>"}
})
→ Current total employees
→ Department distribution
- Track Open Positions
execute("linkedin", "search", "search_jobs", {"keywords": "Competitor Inc", "count": 100})
→ All open positions
→ Use query_cache(cache_key, group_by="location") to group by office
Group by department:
- Engineering roles
- Sales roles
- Marketing roles
- Operations roles
- Analyze Recent Hires
execute("linkedin", "search", "search_users", {
"company_keywords": "Competitor Inc",
"count": 100
})
→ Get all employees
→ Use get_page(cache_key, 10, 100) to paginate through full list
Filter for recent joins:
execute("linkedin", "user", "user_experience", {
"urn": {"type": "fsd_profile", "value": "<profile_id>"},
"count": 5
})
→ Start date at current company
→ Identify hires from last 3-6 months
- Track Key Departures
For former employees:
execute("linkedin", "search", "search_users", {"keywords": "Competitor Inc", "count": 50})
→ Filter profiles showing "Former" or past employment
Identify:
- Leadership departures
- Team exodus (multiple from same department)
- Moves to other competitors
- Competitive Recruiting Analysis
Identify where competitors hire from:
- For each new hire: get previous companies
- Track talent pipelines
- Identify poaching patterns
→ Use export_data(cache_key, "csv") to build a hiring tracker spreadsheet
Expected Output:
- Hiring velocity (hires per month/quarter)
- Department growth priorities
- Key hires and their backgrounds
- Leadership changes
- Talent pipeline insights
Workflow 4: Content Strategy Benchmarking
Scenario: Analyze competitor content across platforms
Steps:
- LinkedIn Content
execute("linkedin", "company", "company_posts", {
"urn": {"type": "company", "value": "<company_id>"},
"count": 50
})
→ Use query_cache(cache_key, aggregate=[{"field": "comment_count", "function": "avg"}]) for engagement stats
Analyze:
- Posting frequency (posts/week)
- Content types (articles, videos, polls)
- Engagement rates (likes, comments, shares)
- Topics and themes
- Employee advocacy (shares/comments from team)
- Twitter/X Content
execute("twitter", "user", "user", {"user": "competitor"})
execute("twitter", "user", "user_posts", {"user": "competitor", "count": 100})
Analyze:
- Tweet frequency
- Engagement metrics
- Content themes
- Use of threads/media
- Response rates
- YouTube Content
execute("youtube", "channel", "channel_videos", {"channel": "competitor", "count": 30})
For each video:
execute("youtube", "video", "video", {"video": "<video_id>"})
Analyze:
- Upload frequency
- View counts
- Engagement (likes, comments)
- Content types (demos, webinars, customer stories)
- Video length and production quality
→ Use query_cache(cache_key, sort_by=[{"field": "view_count", "order": "desc"}]) to find top videos
- Instagram Content (if B2C)
execute("instagram", "user", "user", {"user": "competitor"})
execute("instagram", "user", "user_posts", {"user": "competitor", "count": 50})
Analyze:
- Post frequency
- Visual style/branding
- Engagement rates
- Use of Reels vs. static posts
- Influencer partnerships
- Blog/Website Content
execute("webparser", "parse", "parse", {"url": "https://competitor.com/blog"})
execute("webparser", "sitemap", "sitemap", {"url": "https://competitor.com"})
→ Find all blog posts
Analyze:
- Publishing frequency
- Content topics
- SEO keywords
- Thought leadership positioning
- Community Sentiment
execute("reddit", "search", "search_posts", {"query": "Competitor Inc", "count": 50})
execute("reddit", "search", "search_posts", {"query": "competitor product name", "count": 50})
Analyze:
- Customer feedback
- Common complaints
- Product strengths
- Feature requests
→ Use query_cache(cache_key, sort_by=[{"field": "comment_count", "order": "desc"}]) to find most-discussed threads
Expected Output:
- Cross-platform content strategy matrix
- Engagement benchmarks
- Content themes and messaging
- Platform prioritization insights
- Community sentiment summary
- Use
export_data(cache_key, "csv") for cross-platform content comparison
MCP Tools Reference (v2)
LinkedIn Company Intelligence
Company Profile — execute("linkedin", "company", "company", {"company": "..."})
- Get detailed company profile
- Returns: Description, website, size, industry, specialties, URN
Employee Stats — execute("linkedin", "company", "company_employee_stats", {"urn": {"type": "company", "value": "..."}})
- Get employee statistics and growth
- Returns: Total employees, growth metrics, department distribution
- Note: URN must use
company: prefix (not fsd_company). Convert: urn:li:fsd_company:1441 → company:1441
Company Posts — execute("linkedin", "company", "company_posts", {"urn": {"type": "company", "value": "..."}, "count": N})
- Get recent company posts
- Returns: Posts with engagement metrics, content, timestamps
LinkedIn People Intelligence
Search Users — execute("linkedin", "search", "search_users", {"company_keywords": "...", "title": "...", "count": N})
- Find employees at competitor companies
- Filter by title, department, location
- Returns: Employee profiles with titles and URLs
User Profile — execute("linkedin", "user", "user", {"user": "..."})
- Get detailed employee profile
- Returns: Work history, education, skills
User Experience — execute("linkedin", "user", "user_experience", {"urn": {"type": "fsd_profile", "value": "..."}, "count": N})
- Get detailed work history
- Returns: All positions with dates and descriptions
LinkedIn Jobs
Search Jobs — execute("linkedin", "search", "search_jobs", {"keywords": "...", "count": N})
- Search job listings by keywords, location, and filters
- Returns: Open positions with company, location, work type
Y Combinator Intelligence
Search Companies — execute("yc", "search", "search_companies", {"query": "...", "count": N})
- Search YC companies by industry, batch, filters
- Returns: Company list with batch, team size, status
Company Details — execute("yc", "company", "get", {"slug": "..."})
- Get detailed YC company profile
- Returns: Description, founders, batch, status, links
Search Founders — execute("yc", "search", "search_founders", {"query": "...", "count": N})
- Search for founders by criteria
- Returns: Founder profiles with company associations
Social Media Monitoring
Twitter/X:
execute("twitter", "search", "search_posts", {"query": "...", "count": N}) — Find competitor mentionsexecute("twitter", "user", "user", {"user": "..."}) — Get competitor profileexecute("twitter", "user", "user_posts", {"user": "...", "count": N}) — Get recent tweets
Instagram:
execute("instagram", "search", "search_posts", {"query": "...", "count": N}) — Find hashtag/keyword mentionsexecute("instagram", "user", "user", {"user": "..."}) — Get profile statsexecute("instagram", "user", "user_posts", {"user": "...", "count": N}) — Get recent posts
Reddit:
execute("reddit", "search", "search_posts", {"query": "...", "count": N}) — Find discussions about competitorsexecute("reddit", "posts", "posts", {"post_url": "..."}) — Get post details and sentiment
YouTube:
execute("youtube", "search", "search_videos", {"query": "...", "count": N}) — Find competitor videosexecute("youtube", "channel", "channel_videos", {"channel": "...", "count": N}) — Get all channel videosexecute("youtube", "video", "video", {"video": "..."}) — Get video details and metrics
Web Intelligence
Parse Webpage — execute("webparser", "parse", "parse", {"url": "..."})
- Extract content from competitor websites
- Returns: Text content, links, contacts
Sitemap — execute("webparser", "sitemap", "sitemap", {"url": "..."})
- Get all pages on competitor site
- Returns: URL list for comprehensive analysis
Web Search — execute("duckduckgo", "search", "search", {"query": "..."})
- Search for competitor mentions across the web
- Returns: Search results with URLs and descriptions
Data Analysis Tools (use with any cache_key from execute)
Pagination — get_page(cache_key, offset, limit)
- Load more results beyond first page when
next_offset is returned
Filter/Aggregate — query_cache(cache_key, conditions, sort_by, aggregate, group_by)
- Filter, sort, aggregate cached data without new API calls
- Example:
query_cache(cache_key, sort_by=[{"field": "employee_count", "order": "desc"}])
Export — export_data(cache_key, format)
- Export to "csv", "json", or "jsonl"
- Returns downloadable URL
Output Formats
Chat Summary
Provides competitive intelligence highlights:
- Key findings and insights
- Competitive threats identified
- Growth signals and strategic moves
- Recommended actions
- Top 3-5 competitors to watch
CSV Export
Use export_data(cache_key, "csv") for competitor comparison matrix with:
- Company name, size, location
- Employee count and growth rate
- Posting frequency and engagement
- Key differentiators
- Competitive threat score
JSON Export
Use export_data(cache_key, "json") for complete competitive data for:
- Time-series tracking
- Dashboard visualization
- Automated monitoring
- Integration with BI tools
Advanced Features
Competitive Intelligence Dashboard
Track competitors over time by storing data and comparing:
Monthly Snapshot:
{
"date": "2026-01-29",
"competitors": [
{
"name": "Competitor A",
"employees": 350,
"monthly_growth": 8,
"open_positions": 25,
"linkedin_posts": 12,
"twitter_followers": 5400,
"funding_stage": "Series B"
}
]
}
Trend Analysis:
- Employee growth over 6 months
- Content output changes
- Positioning shifts
- Leadership changes
SWOT Analysis Framework
Strengths (from LinkedIn, website, reviews):
- Team expertise (LinkedIn profiles)
- Product features (website, Reddit feedback)
- Market position (company size, growth)
- Brand recognition (social followers, engagement)
Weaknesses (from reviews, job postings, employee turnover):
- Customer complaints (Reddit, review sites)
- Hiring challenges (multiple re-postings)
- Employee turnover (LinkedIn departures)
- Product gaps (feature requests in forums)
Opportunities (from market analysis):
- Underserved segments (job posting patterns)
- Geographic expansion (new office locations)
- Product expansion (new roles, content themes)
Threats (from competitive monitoring):
- New entrants (YC batch analysis)
- Competitive hiring (talent poaching)
- Product launches (company posts, blogs)
- Pricing changes (website updates)
Win/Loss Analysis
Track deals against specific competitors:
Data Points to Collect:
- Competitor encountered (company name)
- Deal stage (lost/won)
- Key differentiators discussed
- Pricing comparison
- Feature comparison
- Decision factors
Intelligence Gathering:
For each competitor in win/loss:
1. execute("linkedin", "company", "company", {"company": "..."}) → Current positioning
2. execute("webparser", "parse", "parse", {"url": "<website>/pricing"}) → Pricing strategy
3. execute("webparser", "parse", "parse", {"url": "<website>/features"}) → Feature set
4. execute("reddit", "search", "search_posts", {"query": "competitor", "count": 20}) → Customer feedback
5. execute("linkedin", "company", "company_posts", {"urn": {"type": "company", "value": "..."}, "count": 10}) → Recent messaging
Analysis:
- Win rate by competitor
- Common objections
- Competitive advantages/disadvantages
- Pricing positioning
- Feature gaps
Recommendations
For Local/Retail Competitors:
Focus on:
- LinkedIn company presence
- Instagram brand content
- Website location pages
- Reddit community discussions
For Tech/SaaS Competitors:
Excellent coverage through:
- LinkedIn (primary intelligence)
- Y Combinator (for startups)
- Twitter (tech community presence)
- Product Hunt mentions
For Enterprise Competitors:
- LinkedIn extremely comprehensive
- SEC filings for public companies
- Professional social presence
- Limited need for consumer platforms
Reference Documentation
- ANALYSIS_PATTERNS.md - Competitive analysis frameworks, SWOT templates, and intelligence gathering patterns
Troubleshooting
Issue: Competitor Not Found on LinkedIn
Solution:
- Try company name variations
- Search for employees and extract company
- Check if using DBA vs. legal name
- Try website domain search
- Error
412 means not found — check the llm_hint in the response for guidance
Issue: Limited Employee Data
Solution:
- Employees may have privacy settings
- Try searching by title without company filter
- Focus on public leadership team
- Use website team pages as alternative
Issue: No Recent Company Posts
Solution:
- Company may not be active on LinkedIn
- Check Twitter/Instagram instead
- Use website blog for content analysis
- Focus on employee posts mentioning company
Issue: URN Format Errors (422)
Solution:
- Company sub-endpoints require
company: prefix, NOT fsd_company
- Convert:
urn:li:fsd_company:1441 → use {"type": "company", "value": "1441"}
- User sub-endpoints require
fsd_profile URN from /linkedin/user response
- Always get URNs from the parent endpoint response first
Ready to analyze competitors? Ask Claude to help you research competitors, track hiring patterns, or benchmark competitive positioning using this skill!
