"A method for finding people on LinkedIn based on company name" matching MCP servers:

A template for deploying an MCP server on Vercel, with example tools like roll_dice and get_weather.

Enables assistants to publish readable replies and status updates to e-ink displays and Home Assistant, with switchable characters and state retrieval through MCP tools.

An MCP server that gives AI agents a private, durable memory of people, providing a personal people graph in PostgreSQL with tools to search, remember, and connect people, plus imports from LinkedIn, Google Contacts, and WhatsApp, and a browser UI.

Open MCP server for AI agents to discover people, jobs, collaborators and projects through semantic search over human-published context.

Enables AI agents to query and manage company knowledge from a Supabase GraphRAG store, including accounts, meetings, people, org hierarchy, product docs, and call logs.

Exposes nine governed analytics tools — attrition, headcount, tenure, salary, promotion, and more — plus a restricted read-only SQL execution path, so an HR analyst's plain-English question resolves to a versioned, reproducible method instead of free-form LLM-written SQL. Tool selection is driven by the LLM, while role-based access control, PII screening, SQL guards, result validation, and audit logging keep every answer within policy.

Enriches domains into full company profiles with firmographics and buying signals.

模糊匹配两份表格中的公司名称和日期，输出已匹配、待复核和未匹配三种结果，便于数据对账。

Enables AI assistants to publish text, link, and image posts to a personal LinkedIn profile, as well as comment, react, and delete posts, through the official LinkedIn API.

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.

An unofficial Model Context Protocol server enabling AI assistants to access LinkedIn profile data, network connections, search people and jobs, and send messages via OAuth 2.1.

Dynamic tools to automate tasks on LinkedIn website.

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 LinkedIn, enabling posting, liking, commenting, and profile retrieval via official OAuth 2.0. Features CLI, HTTP admin, and optional Telegram bot.

Enables sending LinkedIn messages and invitations, reading conversations, and managing outreach through natural language by automating a real LinkedIn session via a Chrome extension.

An MCP server providing generic browser automation and HTTP primitives for operating a LinkedIn session, supporting local Chromium or cloud browsers, with deterministic tools and optional AI tasks.

MCP server that lets AI agents operate a real LinkedIn account in plain English with safety controls and approval queues.

Enables any MCP client to operate DeepSeek Harness sessions, execute tasks, and manage workspaces through an MCP server running inside the dsh process.

A throwaway HTTP MCP server that empirically tests whether Cursor invokes tools by exact name or munges them, to inform case normalization decisions.

Enables job search on LinkedIn through MCP tools, including keyword and location search, filtering by remote, easy apply, experience level, job type, and date, and retrieving job details.