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@maheidem/linkedin-mcp

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    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    B3.4/5.0

    Scored across 13 tools

    Disambiguation4/5

    Most tools are clearly distinct, but there is some overlap between linkedin_create_post, linkedin_create_optimized_post, and linkedin_post_profile_update, which all create posts. The first two are distinguished by optimization, but the third could be confused as a different action. Overall, boundaries are mostly clear.

    Naming Consistency5/5

    All tools follow a consistent linkedin_verb_noun pattern using snake_case. Verbs like create, get, generate, and post are used predictably. The naming is uniform and easy to parse, with no mixing of conventions.

    Tool Count5/5

    With 13 tools, the server covers a substantial but focused set of LinkedIn operations—auth, profile, posts, feed, comments, and activity. This is well within the typical 3-15 range and feels complete without being bloated.

    Completeness4/5

    The tool surface covers the main LinkedIn use cases (auth, profile, posts, feed, comments, activity, optimization). Minor gaps exist, such as lacking update/delete operations for posts or comments, but the core workflows are supported and agents can operate without major dead ends.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources