Linkedin Mcp Server
A LinkedIn MCP server to find jobs, search people, research companies, manage your network, publish and engage with posts, and read or send messages.
Find MCP servers that connect AI assistants to useful tools and data. Explore what each server does, its setup and its documentation.
2781 servers · Page 182 of 232
A LinkedIn MCP server to find jobs, search people, research companies, manage your network, publish and engage with posts, and read or send messages.
Give your AI agent a full Chrome workspace. 70 MCP tools powered by nodriver: browse, extract data, capture network traffic and inspect security.
MCP server for Football Charts — football data for 93 leagues in 42 countries: results, fixtures, tables, goal timing and model probabilities. 10 tools…
Compiler-precise code property graph for C, Python, and TypeScript, navigable over MCP — data- and taint-flow with source→sink witnesses, points-to…
Google Flights MCP server by HasData: fares, flight legs, carbon emissions and price history, as JSON. 1 tools, with
Hosted Google Maps MCP server from HasData, no Google Cloud project needed. Search places, reviews, contributor history, photos and posts for Claude… 6 tools…
Official BestPrice.gr MCP server. It gives AI assistants read-only shopping decisions (evidence-backed recommendations and basket plans), product… 4 tools, with
Deploy and operate self-hosted OpenClaw on AWS, GCP, Azure or your own VM, from the command line or from your agent. 30 tools, with
Windows computer-use MCP server for dsh (DeepSeek Harness) — client-neutral, works with any stdio MCP client.
Auth Your Agent: let AI agents act for a person on websites, with the person's approval on their phone.
A tunneled MCP that let's ChatGPT web and dot use your local machine.
LayerMap MCP: a layered map of your codebase for coding agents: callers, callees and the impact of a change, for TypeScript, JavaScript, Go, Python…
An MCP server exposes tools or data through the Model Context Protocol so a compatible AI client can use them. Each project has its own installation, authentication and permission requirements.
Open a server’s page for its getting-started notes, compatibility and sources, then follow the original project’s documentation for your AI client.
Entries link to the original documentation. Check access requirements, costs and maintenance there before installing, and grant a server only the access it needs.