mcp-server-linkedin
Related Servers
Alternatives to mcp-server-linkedin
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityDmaintenanceEnables Claude AI to interact with LinkedIn through browser automation, including profile reading, people and job search, company research, post publishing, and profile editing.MIT
- AlicenseAqualityCmaintenanceConnects LinkedIn to AI assistants, enabling lead search, profile analysis, messaging, and workflow automation through a cloud browser. Supports sales, recruiting, and market research tasks.59652 npmMIT
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to use an existing browser session to read profiles and companies, search jobs and people, and manage messages and connection requests on LinkedIn.Apache 2.0
- AlicenseAqualityCmaintenanceEnables AI assistants to browse profiles and companies, manage messages and inboxes, and search jobs, posts, and people through a locally logged-in browser session. All actions run on the user's own machine.19Apache 2.0
- AlicenseBqualityDmaintenanceConnects Claude Desktop to LinkedIn's data layer for AI-powered networking, enabling profile research, content creation and scheduling, engagement automation, analytics tracking, and messaging through natural language.8544MIT
- AlicenseAqualityAmaintenanceEnables AI assistants to interact with LinkedIn by scraping profiles, companies, job postings, and getting personalized job recommendations using authenticated browser automation.1711,396 PyPI4,044Apache 2.0
TDQS
Scored across 47 tools
Most tools map to a distinct resource+action (posts, jobs, invitations, messaging, profile, settings), so an agent can generally pick correctly. There is some overlap: connect_with_person claims it can also accept an incoming request, colliding with accept_invitation, and create_post vs create_post_with_image differ only by media attachment, but these are minor and descriptions clarify them.
Nearly every tool follows a clean verb_noun snake_case pattern (get_company_posts, create_post, delete_post, accept_invitation, search_jobs, update_headline). The few noun-leading outliers like close_session and debug_profile_controls still read as consistent imperative names, so the pattern is predictable throughout.
47 tools is very heavy for this surface and well past the 25+ threshold. While the LinkedIn domain is broad, the set is inflated by granular settings tools (list_settings_sections, get_setting, update_setting) and an internal debug_profile_controls that most agents would never need, suggesting the surface could be meaningfully consolidated.
Coverage is strong across posts, comments/reactions, jobs, invitations/connections, messaging, feed, and profile editing, covering the main write and read lifecycles. Minor gaps remain, such as listing your own connections/followers or retrieving your own authored posts, but these are workable limitations rather than dead ends.