"How to find people on LinkedIn using their profiles" matching MCP servers:

A minimal MCP server with get_weather and create_ticket tools, used for testing MCP servers across protocol, unit, eval, transport, and auth layers.

Enables building RudderStack Profiles projects using natural language through AI assistants, supporting data discovery, identity resolution, feature engineering, and propensity modeling.

An MCP server that reads and edits OrcaSlicer profiles, expanding the full inheritance chain and tracking the provenance of every value.

A Model Context Protocol (MCP) server that automates generating LinkedIn post drafts from YouTube videos. This server provides high-quality, editable content drafts based on YouTube video transcripts.

MCP server for querying a database of 1 million Korean personas with full-text search, enabling AI agents to retrieve detailed demographic, professional, and personal profiles.

Provides an MCP server that tracks open loops (pending decisions or replies) across email, agent sessions, and other channels, enabling agents to query what is waiting on whom.

A discovery tool for AI agents to search, evaluate, and install MCP servers from multiple registries.

Enables fetching weather forecasts for the USA via NWS API and for Israel via browser automation using Playwright.

Enables Claude Code users to safely edit their own LinkedIn profile by drafting proposed changes as diffs and requiring explicit human approval before the single write tool applies them.

Enables AI assistants to search LinkedIn jobs and read LinkedIn profiles read-only using a real Chrome session via CDP, with tools for job listings, full job details, profile data, and session management.

Enables viewing your own LinkedIn account data—such as profile views, applications, saved jobs, job listings, and notifications—as structured tool results, with optional gated write actions for saving or unsaving jobs and unfollowing companies.

A standalone MCP server that exposes typed LinkedIn capabilities (jobs, people, companies, posts, invitations, messaging) through the visible LinkedIn web UI, enabling workflow automation.

Enables searching and scraping of LinkedIn for structured data on people, companies, and job listings. It allows AI clients to retrieve detailed profiles, experience, and activity sections using browser automation.

Enables AI assistants to read LinkedIn profiles, company pages, jobs, messages, and feed through a user's logged-in browser session.

Enables Claude to access and analyze LinkedIn profile data through the Model Context Protocol, allowing users to query their LinkedIn information directly within Claude Desktop.

Enables AI assistants to interact with LinkedIn by scraping profiles, companies, job postings, and getting personalized job recommendations using authenticated browser automation.

Enables publishing and scheduling LinkedIn posts through the official API, with content calendar and post brief tools for consistent growth.

MCP server that enriches LinkedIn profiles, companies, and enables people search using the Techtenstein LinkedIn Enrichment API.

Enables AI assistants to connect to LinkedIn, accessing profiles and companies, searching for jobs and people, managing saved jobs, updating job-search profile settings, and inspecting analytics.

MCP server that lets you analyze your own LinkedIn profile with a local LLM (LM Studio). It uses Playwright to reuse your browser session, fetch profile data as JSON, and provides tools for session management and profile analysis.