LinkedIn MCP Pro Max
Related Servers
Alternatives to LinkedIn MCP Pro Max
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityBmaintenanceA production-ready MCP server that enables AI agents to autonomously create, manage, and engage with LinkedIn content through the official LinkedIn REST API.74 npm2MIT
- AlicenseAqualityDmaintenanceFully featured MCP server that provides automation tools for LinkedIn, supporting browser-based scraping and API-based operations for content management, media uploads, and reactions.63MIT
- AlicenseNot gradedqualityCmaintenanceAI-powered LinkedIn automation server for content generation, profile/company data extraction, and connection request automation, integrating with MCP clients like Claude Desktop.MIT
- AlicenseNot gradedqualityCmaintenanceMCP server for programmable LinkedIn automation via Playwright, offering 20 tools for profile management, messaging, feed interaction, and job searching through real browser automation.13 npmMIT
- AlicenseAqualityCmaintenanceSelf-hosted, ban-safe MCP server for LinkedIn that provides 22 tools for profiles, search, jobs, posts, connections, and messages. Integrates with any MCP-compatible client like Claude Desktop.581MIT
- AlicenseBqualityCmaintenancePlaywright-powered MCP server for LinkedIn that automates jobs, profile edits, messaging, network actions, and feed posts using a real logged-in browser session.36Apache 2.0
TDQS
Scored across 14 tools
Most tools have clearly distinct purposes (e.g., interact_with_post vs create_linkedin_post, job vs application). Some minor overlap exists between generate_resume and tailor_resume, but descriptions clarify the distinction. Profile and its sub-section tools (experience, skills, education) are logically separated but could be slightly ambiguous.
Naming conventions are mixed: some tools are verb_noun (create_linkedin_post, generate_resume, list_templates), while others are bare nouns (job, profile, company, experience, skills, education, server, application). This inconsistency makes the tool set feel less predictable, even though the noun tools share a pattern of action-based arguments.
With 14 tools, the server covers a broad but well-scoped set of LinkedIn features (posts, jobs, profiles, resumes, applications). The count is within the ideal 3-15 range and each tool addresses a meaningful function without redundancy.
The server covers core LinkedIn workflows: profile management (experience, skills, education), job search/apply, post creation/interaction, and resume/cover letter generation. Minor gaps exist, such as no post deletion or edit, and no direct messages/connections, but these are not critical for the apparent job-seeker focus.