"A platform for finding jobs on LinkedIn" matching MCP servers:

Enables users to search LinkedIn's public job listings with advanced filters like location, salary, and experience level. It allows MCP-compatible clients to retrieve real-time job opportunities without requiring LinkedIn authentication or API keys.

An MCP server that lets AI assistants like Claude read LinkedIn data through your own logged-in browser session. Access profiles and companies, search for jobs, or get job details.

MCP server for live US software-engineering job search from public ATS boards, with tools to search jobs and list sources.

Enables LinkedIn profile reads and post operations through a local-first MCP server, with OAuth token management and approval-friendly tools for OpenWorker.

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.

An MCP server for searching UK tech jobs from the winterchill catalog, enabling job search, company lookup, and CV matching/tailoring via LLM agents.

Enables asking what companies are hiring right now by querying live job postings from their applicant-tracking system board APIs (Greenhouse, Lever, Ashby, Recruitee, Rippling, Personio), with filters, parsed location, remote flag, and structured salary.

Lets an AI assistant read and write business records in plain language, including looking up people, creating and updating tasks, logging time, and pulling utilization reports through a synthetic ops platform or an optional ClickUp adapter.

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 querying open job postings directly from company applicant-tracking systems (Greenhouse, Ashby, Lever), finding a company's job board, listing and comparing roles, and accessing salary data, all without scraping or API keys.

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 local MCP server that lets Claude log in to LinkedIn and publish image posts to your personal profile feed, backed by LinkedIn's REST Images API and Posts API.

MCP server for Argo CD and Vault that allows authenticated users to run CLI commands via GitLab SSO, with confirmation for dangerous operations and secret redaction from model context.

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

MCP server for LinkedIn publishing from AI coding assistants. Dry run by default, SKILL.md for safe workflows, 28 unit tests. MIT licensed.

Enables AI agents to publish text and link posts, comment, react, and delete posts on LinkedIn through the official OAuth API, with every write gated behind human approval via a two-phase prepare/execute flow. Includes exact-match digests, single-use expiring proposals, daily write caps, and private local token storage with zero third-party dependencies.

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.

MCP server that posts to LinkedIn through the LinkedIn API. Enables creating text posts on your LinkedIn profile using natural language from any MCP-compatible client.

Enables Claude to manage your LinkedIn account and pages (post, schedule, read feed, comments) by driving a real local Chrome browser under your logged-in session.

Enables an MCP client such as Claude Code to search LinkedIn jobs, read postings and profile data, track what has been seen, and prepare actions on a user's own account. Every consequential LinkedIn action requires explicit out-of-band confirmation in a terminal, with typed tools and failure-honest errors.