linkfetch-mcp
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- AlicenseNot gradedqualityDmaintenanceEnables AI assistants to search LinkedIn jobs with built-in rate limiting to prevent IP bans. Supports job search, filtering, company profiles, and job categories through MCP tools.MIT
- AlicenseAqualityDmaintenanceEnables searching and scraping of LinkedIn profiles, companies, jobs, and posts using natural language through MCP-compatible AI clients.13MIT
- FlicenseNot gradedqualityDmaintenanceEnables AI agents to interact with LinkedIn through MCP tools for retrieving company profiles, posts, insights, and person profiles, as well as a prompt for account research.-
- AlicenseAqualityBmaintenanceEnables 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.20MIT
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TDQS
Scored across 24 tools
Tools mostly target distinct resources (profile, company, job, post, group, conversation) and actions (get, search, list, read). A few pairs like get_job vs get_job_by_url and safety_status vs safety_limits could be momentarily confused, but descriptions clarify input types and scope.
All tools share the linkfetch_ prefix and predominantly follow verb_noun (get_profile, search_jobs). Exceptions like jobs_database_info, safety_status, and linkedin_connection use noun phrases, but overall consistency is high.
24 tools is on the heavy side for a single MCP server, though the breadth of LinkedIn data (profiles, companies, jobs, posts, groups, messaging, safety) justifies some expansion. Still, it sits in the borderline 16-25 range.
The surface covers read operations across major LinkedIn entities and includes safety/connection status, but lacks any write actions (e.g., send message, connect, create post) despite safety limits implying those actions exist. This is a notable gap for a server that appears to enable LinkedIn interactions.