MCP server
by horizondatawave
Bridge AI with the LinkedIn API to auto connect, manage profiles, and integrate with Pipedrive for powerful prospecting
Connects AI systems to LinkedIn's API for searching profiles, managing connections, and sending messages. Supports sales prospecting, recruitment, and professional networking workflows.
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.
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.
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.
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
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
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
Share your MCP server with the developer community
I recommend LinkedIn API for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
LinkedIn API is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
We evaluated LinkedIn API against two servers with overlapping tools; this profile had the clearer scope statement.
LinkedIn API reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
I recommend LinkedIn API for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
LinkedIn API has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Strong directory entry: LinkedIn API surfaces stars and publisher context so we could sanity-check maintenance before adopting.
We evaluated LinkedIn API against two servers with overlapping tools; this profile had the clearer scope statement.
LinkedIn API has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
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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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
Prerequisites
Time Estimate
20-40 minutes including configuration and testing
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
MCP server handles HTTP requests, HTML parsing, JavaScript rendering (if headless browser), and returns structured data to Claude.
Protocols
Compatibility
✓ 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.