LinkedIn API▌
by horizondatawave
Bridge AI with the LinkedIn API to auto connect, manage profiles, and integrate with Pipedrive for powerful prospecting
Bridges AI systems with LinkedIn's API for searching users, retrieving profiles, accessing posts, managing connections, and sending messages to support sales prospecting, recruitment, and professional networking workflows.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Sales teams doing prospect research
- / Recruiters sourcing candidates
- / Marketing teams building contact lists
- / Business development professionals
capabilities
- / Search LinkedIn users and companies
- / Retrieve detailed LinkedIn profiles
- / Access LinkedIn posts and content
- / Manage LinkedIn connections
- / Send LinkedIn messages
- / Extract profile data for lead generation
what it does
Connects AI systems to LinkedIn's API for searching profiles, managing connections, and sending messages. Supports sales prospecting, recruitment, and professional networking workflows.
about
LinkedIn API is a community-built MCP server published by horizondatawave that provides AI assistants with tools and capabilities via the Model Context Protocol. Bridge AI with the LinkedIn API to auto connect, manage profiles, and integrate with Pipedrive for powerful prospecting It is categorized under search web.
how to install
You can install LinkedIn API in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
MIT
LinkedIn API is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
Claude Desktop (Click to expand)
1. Open **Claude Desktop** → **Settings** → **Connectors** 2. Click **Add Custom Connector** 3. Fill in: - **Name:** Anysite MCP - **OAuth URL:** `https://mcp.anysite.io/` 4. Click **Add** → **Connect** → **Allow Access** 📖 [Detailed Claude Desktop Setup Guide](https://docs.anysite.io/mcp-server/claude-desktop-tool/installation)Cline / Cursor / Windsurf
Add to your MCP configuration file: ```json { "mcpServers": { "anysite": { "command": "npx", "args": ["-y", "@anysite/mcp"], "env": { "ANYSITE_OAUTH_URL": "https://mcp.anysite.io/mcp" } } } } ``` Configuration file locations: - **Cline:** `.cline/mcp_settings.json` - **Cursor:** `.cursor/mcp_config.json` - **Windsurf:** `.windsurf/mcp_config.json`Web Search (1 tool)
- `duckduckgo_search` - Web search powered by DuckDuckGo (up to 20 results)Y Combinator (3 tools)
- `get_yc_company` - Get comprehensive YC company information by slug - `search_yc_companies` - Search YC companies with filters (batch, status, industry) - `search_yc_founders` - Search YC founders by name, company, batch, industryYouTube (3 tools)
- `search_youtube_videos` - Search YouTube videos by query - `get_youtube_video` - Get detailed video information by ID or URL - `get_youtube_video_subtitles` - Extract video subtitles with timestampsSEC (2 tools)
- `search_sec_companies` - Search SEC EDGAR filings with advanced filters - `get_sec_document` - Retrieve full SEC document content by URLLinkedIn Tools (35 tools)
**Search & Discovery (11 tools)** - `search_linkedin_users` - Advanced user search with 10+ filters - `linkedin_sales_navigator_search_users` - Sales Navigator advanced search - `search_linkedin_companies` - Search companies with advanced filters - `search_linkedin_educations` - Search educational institutions for filtering - `search_linkedin_industries` - Search industries for filtering - `search_linkedin_locations` - Search locations for filtering - `search_linkedin_jobs` - Search job postings with filters - `find_linkedin_user_email` - Find users by email address - `get_linkedin_user_email_db` - Get email from internal database (up to 10 profiles) - `get_linkedin_google_company` - Find companies via Google search - `get_linkedin_company` - Company details lookup **User Profiles & Details (12 tools)** - `get_linkedin_profile` - Full profile with experience, education, skills - `get_linkedin_user_posts` - User's post history - `get_linkedin_user_comments` - User's comment history - `get_linkedin_user_reactions` - Posts user reacted to - `get_linkedin_user_endorsers` - Skill endorsers - `get_linkedin_user_certificates` - Professional certificates - `get_linkedin_user_education` - Education history - `get_linkedin_user_experience` - Work experience details - `get_linkedin_user_skills` - Skills and endorsements - `get_linkedin_user_honors` - Awards and honors - `get_linkedin_user_patents` - Patent information - `get_linkedin_user_languages` - Language proficiencies **Company Information (4 tools)** - `get_linkedin_company_employee_stats` - Employee statistics - `get_linkedin_company_employees` - Employee list with filters - `get_linkedin_company_posts` - Company updates - `get_linkedin_management_company_ ---FAQ
- What is the LinkedIn API MCP server?
- LinkedIn API is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for LinkedIn API?
- This profile displays 72 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.7 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Web Research & Information Gathering
Fetch and extract information from websites automatically
Example
Research competitor pricing, scrape product reviews, monitor news mentions
Automate 5-10 hours/week of manual web research
Content Monitoring & Alerts
Track website changes, new content, price updates
Example
Monitor competitor blog for new posts, track stock availability, watch for pricing changes
Stay informed without manual checking, never miss important updates
Data Extraction & Aggregation
Extract structured data from multiple websites
Example
Compile product listings from 10 e-commerce sites, aggregate job postings, collect real estate data
Build datasets 100x faster than manual copying
API-less Integration
Interact with services that don't offer APIs
Example
Check form submissions, validate website functionality, test user flows
Automate interactions with any website, even without API
Implementation Guide▌
Prerequisites
- ›Claude Desktop or Cursor with MCP support
- ›Understanding of web scraping ethics and robots.txt
- ›Rate limiting awareness to avoid overwhelming target sites
- ›Knowledge of legal restrictions on data collection
Time Estimate
20-40 minutes including configuration and testing
Installation Steps
- 1.Install web automation MCP server via npm or pip
- 2.Configure allowed domains and rate limits in MCP config
- 3.Test with simple fetch: 'Get content from example.com'
- 4.Progress to extraction: 'Extract all product prices from this page'
- 5.Set up monitoring: 'Check this URL daily for changes'
- 6.Parse structured data: 'Create CSV from this table'
- 7.Respect robots.txt and rate limits always
Troubleshooting
- ⚠403 Forbidden: Website blocks bots—respect their wishes, use official API instead
- ⚠Rate limit errors: Slow down requests, add delays between fetches
- ⚠Stale data: Target site changed HTML structure—update selectors
- ⚠Timeout errors: Site is slow or blocking—increase timeout, try different user agent
- ⚠JavaScript-rendered content: Use headless browser MCP servers for dynamic sites
Best Practices▌
✓ Do
- +Check robots.txt and respect crawl rules
- +Rate limit requests: 1-2 requests/second maximum
- +Use official APIs when available instead of scraping
- +Identify your bot with descriptive user agent
- +Cache results to minimize repeated requests
- +Handle errors gracefully with retries and fallbacks
- +Validate extracted data for accuracy
✗ Don't
- −Don't scrape sites that explicitly forbid it (robots.txt, ToS)
- −Don't overwhelm servers with rapid requests—use rate limiting
- −Don't scrape personal data without consent and legal basis
- −Don't ignore copyright on extracted content
- −Don't assume HTML structure is stable—handle changes
- −Don't use scraped data for commercial purposes without permission
💡 Pro Tips
- ★Use CSS selectors or XPath for robust data extraction
- ★Set up monitoring alerts for extraction failures (structure changed)
- ★Implement exponential backoff for retries on failures
- ★Store raw HTML for reprocessing if extraction logic changes
- ★Combine with data analysis tools for insights from extracted data
- ★Consider using official APIs or RSS feeds as more stable alternatives
Technical Details▌
Architecture
MCP server handles HTTP requests, HTML parsing, JavaScript rendering (if headless browser), and returns structured data to Claude.
Protocols
- HTTP/HTTPS
- WebSocket (for real-time sites)
- Puppeteer/Playwright (for JavaScript sites)
Compatibility
- Static HTML sites
- JavaScript-rendered SPAs (with headless browser)
- REST APIs
- GraphQL endpoints
When to Use This▌
✓ Use When
Use for research automation, content monitoring, data aggregation from multiple sources, and when official APIs don't exist. Best for read-only information gathering.
✗ Avoid When
Avoid for sites with APIs (use API instead), sites that explicitly forbid scraping, when data is copyrighted, or for login-required content without proper authorization.
Integration▌
- →Scheduled monitoring with change detection
- →Multi-source data aggregation pipelines
- →Fallback to web scraping when API rate limits hit
- →Headless browser for JavaScript-heavy sites
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
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Ratings
4.7★★★★★72 reviews- ★★★★★Sofia Gill· Dec 28, 2024
I recommend LinkedIn API for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Michael Iyer· Dec 16, 2024
LinkedIn API is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Mateo Yang· Dec 16, 2024
We evaluated LinkedIn API against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Li Huang· Dec 16, 2024
LinkedIn API reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Zaid Farah· Dec 12, 2024
I recommend LinkedIn API for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Ganesh Mohane· Dec 4, 2024
LinkedIn API has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Michael Ghosh· Nov 23, 2024
Strong directory entry: LinkedIn API surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Nia Ramirez· Nov 19, 2024
We evaluated LinkedIn API against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Naina Reddy· Nov 15, 2024
LinkedIn API has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Naina Rao· Nov 7, 2024
We wired LinkedIn API into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
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