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VisiblyAI MCP Server

by AntonioBlago
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Python
Hybrid

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    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

    C2.8/5.0

    Scored across 84 tools

    Disambiguation2/5

    Many tools have overlapping purposes: score_text, optimize_content_draft, and run_content_optimizer all evaluate/improve content; classify_keywords_simple and classify_keywords_advanced do nearly the same thing; get_content_query, list_content_queries, and get_content_status all read query state; seo_agent and seo_workflow both run multi-step SEO tasks. An agent would struggle to pick the right one without deep inspection.

    Naming Consistency2/5

    Naming mixes verb_noun (list_articles, create_content_query), noun-only (recall, remember, seo_checklist), and noun_verb (score_text, check_serp, query_search_console) patterns. Similar functions get different styles, e.g. optimize_content_draft vs run_content_optimizer, and get_gsc_clusters vs get_content_query, making the surface hard to predict.

    Tool Count1/5

    84 tools is far beyond a reasonable scoped surface for an SEO/content platform. The set feels like several products bolted together (scoring, CMS, optimizer, GSC, analytics, SERP data, agents, memory, meeting import) with many redundant variants, guaranteeing confusion and high selection cost.

    Completeness4/5

    The surface covers most lifecycle operations: content queries (create/read/save/generate/optimize), articles (create/edit/status/publish/backup/restore), CMS connections (CRUD/test), optimizer suggestions (list/approve/reject/undo), and analytics. Minor gaps exist, such as no delete_article or bulk operations, but core workflows are well supported.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources