Linked API MCP
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- AlicenseAqualityDmaintenanceAn 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.19Apache 2.0
- AlicenseAqualityDmaintenanceAn 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.17Apache 2.0
- AlicenseNot gradedqualityDmaintenanceAI-powered LinkedIn automation server for content generation, profile/company data extraction, and connection request automation, integrating with MCP clients like Claude Desktop.MIT
- FlicenseNot gradedqualityCmaintenanceHosted LinkedIn MCP server that connects AI apps to a user's own LinkedIn account, enabling inbox reading, messaging, invitations, people search, and post interactions.2-
- AlicenseAqualityNot gradedmaintenanceAn MCP server that lets AI assistants read LinkedIn data through the user's logged-in browser session, providing tools for profiles, companies, job searches, messaging, and feeds.19Apache 2.0

LinkMCPofficial
AlicenseNot gradedqualityBmaintenanceHosted LinkedIn MCP server that connects your own LinkedIn account to any MCP client, providing 33 tools for research, search including Sales Navigator, profiles, inbox, posts, connections, and email or mobile finding. Enables AI-driven prospecting, outreach, engagement, and recruiting workflows with built-in rate limits and account safety.3MIT
TDQS
Scored across 37 tools
Each tool targets a distinct action or domain (admin, standard LinkedIn, Sales Navigator) with clear descriptions. Overlapping functions like fetch_person vs nv_fetch_person are disambiguated by the platform context.
Tool names follow a consistent snake_case pattern with prefixes (admin_, nv_) to indicate scope, and plain verbs for standard LinkedIn. This pattern is predictable and aids tool selection.
With 37 tools, the count exceeds the 25+ threshold, making it feel heavy. While the server aims to cover LinkedIn comprehensively, a more modular split (e.g., separate admin, standard, and Sales Navigator servers) could improve coherence.
Covers most core LinkedIn actions (posts, messages, connections, search, admin) but lacks explicit tools for accepting connection requests or managing groups, leaving minor gaps.