MCP-LinkedIn
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Alternatives to MCP-LinkedIn
No user-submitted related servers found.
Related Servers
- FlicenseNot gradedqualityCmaintenanceEnables AI assistants to manage LinkedIn workflows through a comprehensive set of tools for content generation, profile optimization, lead management, message outreach, engagement, analytics, scheduling, and industry research.-
- FlicenseAqualityCmaintenanceAutomates LinkedIn B2B marketing tasks such as profile search, company analysis, and connection request drafting, with optional AI-powered features via DeepSeek.5-
- AlicenseAqualityAmaintenanceEnables AI assistants to interact with LinkedIn by scraping profiles, companies, job postings, and getting personalized job recommendations using authenticated browser automation.1715,550 PyPI3,593Apache 2.0
- AlicenseNot gradedqualityAmaintenanceProvides LinkedIn automation via a real browser session using your own cookie, enabling profile, company, job, and post search and reading, plus sending messages and connection requests with rate limiting.72 PyPI2MIT
- AlicenseAqualityAmaintenanceEnables AI assistants to search leads, view profiles, manage lists, send InMails, and export data from LinkedIn Sales Navigator through browser automation.89MIT
- FlicenseNot gradedqualityDmaintenanceEnables users to search for jobs, retrieve profiles, and fetch feed posts through the LinkedIn API. It also provides tools for analyzing and extracting data from PDF resumes.-
TDQS
Scored across 6 tools
Each tool has a clearly distinct purpose with no overlap: close_session handles session management, get_company_profile and get_person_profile target different entity types, while get_job_details, get_recommended_jobs, and search_jobs cover different job-related operations. The descriptions clearly differentiate between retrieving specific entities versus searching/recommending.
All tools follow a consistent verb_noun naming pattern: close_session, get_company_profile, get_job_details, get_person_profile, get_recommended_jobs, and search_jobs. The pattern is uniform throughout with 'get_' or action verbs followed by descriptive nouns, making the set predictable and readable.
Six tools is a reasonable count for a LinkedIn-focused server, covering core operations like profile retrieval, job search, and session management. It's slightly lean but well-scoped; minor additions like update operations or more entity types could enhance it without being necessary.
The toolset covers key read operations for profiles and jobs, but lacks update, create, or delete capabilities typical in social media contexts (e.g., posting updates, sending messages). While agents can retrieve data, they cannot interact or modify content, which limits workflow completeness for a full LinkedIn integration.