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linkedin-mcp

by AryanRajMaurya
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Python
Hybrid

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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

    A4/5.0

    Scored across 5 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose: reading the profile, updating it, checking a draft post, publishing a post, and inspecting token status. The get/update and check/publish pairs are naturally separated by read-vs-write and validate-vs-execute semantics. There is no meaningful overlap that would cause misselection.

    Naming Consistency4/5

    All tools use the linkedin_ prefix and mostly follow a verb_noun pattern: update_profile, check_post, publish_post, get_profile. linkedin_token_status is a noun-style status tool rather than a verb-led action, which is a minor but sensible deviation.

    Tool Count5/5

    Five tools is well-scoped for a LinkedIn profile-and-posting server. Each tool earns its place across the read, validate, publish, update, and auth-diagnostic workflow.

    Completeness4/5

    The surface covers the core lifecycle: read profile, update profile, validate a draft, publish it, and diagnose token scopes. Minor gaps remain around managing already-published posts, such as listing, editing, or deleting them, but the main workflows are covered.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources