"LinkedIn professional networking platform" matching MCP servers:

Low-token MCP server for HPE Networking automation, enabling search of Aruba/HPE docs, OpenAPI details, Central health checks, troubleshooting workflows, configuration management, and guarded ArubaOS 8 migrations and GreenLake Platform operations across platforms like Aruba Central, ClearPass, Mist, and Apstra.

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 MCP-capable agents to read and update a LinkedIn profile, check and publish posts through the official LinkedIn API. Includes a built-in quality gate that blocks drafts reading as machine-generated before anything reaches the public feed.

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.

Lets an AI assistant operate LinkedIn through an authenticated browser session, enabling profile management, posting, networking, messaging, job search, and automated applications.

Dynamic tools to automate tasks on LinkedIn website.

Enables compatible LLM clients to handle authorized professional-network workflows via OAuth, retrieve basic profiles, draft profile changes and posts, and publish posts only after explicit approval.

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.

A self-hosted platform that aggregates upstream MCP servers, OpenAPI imports, and remote device connectors behind a single endpoint per profile, with per-agent scoped authorization, tool/prompt/resource catalogs, and approval-based temporary permissions. It also lets administrators distribute skills and connectors to paired devices and export client configurations.

A shared communication bus for multiple agents using NATS and MCP, enabling MCP clients to list, message, and query agents.

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

Local-first MCP server using LinkedIn's official OAuth and REST APIs to connect a member account, read profile, and publish text posts.

Enables AI assistants to interact with the Open Targets Platform API to search and retrieve comprehensive data about target-disease associations, drugs, genes, and drug discovery information through GraphQL queries.

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.

Released 3.0.0: 22 MCP tools, guided offline setup, local stdio, Chrome and manual login. No hosted deployment or job-research brief. Writes need opt-in, reviewed preview and human approval. Unofficial; provider compatibility, first-use cohorts, coordinated erasure and Windows privacy proof remain unverified. No mandatory paid service.

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.

The Problem Modern distributed systems and AI agents require robust operational scaffolding. Simple CRUD apps or mock loops fail when subjected to real-world edge cases, asynchronous boundaries, and security constraints. The Solution An isolated execution platform for AI agents. An agent is given a broken service and a bounded toolset inside a disposable sandbox. Every command passes throug