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gabrielbelli

pelando-mcp

by gabrielbelli
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

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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 9 tools

    Disambiguation5/5

    Each tool targets a distinct action+resource: search_deals vs browse_feed are separated by query-based vs community-feed retrieval, search_stores vs get_store_coupons split merchant lookup from coupon codes, and get_deal/get_deal_comments/assess_deal_quality are clearly layered. Descriptions explicitly state boundaries and upstream limitations, leaving little room for misselection.

    Naming Consistency5/5

    Uniform snake_case verb_noun pattern throughout (search_deals, browse_feed, get_deal, get_deal_comments, assess_deal_quality, search_stores, get_store_coupons, list_communities, ping). Verbs are used consistently and predictably for their intent.

    Tool Count5/5

    Nine tools is well within the ideal 3-15 range and each one maps to a distinct capability (search, browse, fetch, comments, quality, stores, coupons, taxonomy, liveness). No filler or redundant tools.

    Completeness4/5

    The read-only deal-consumption surface is thorough: discovery (search/browse), retrieval (deal/comments), trust assessment, stores, coupons, and taxonomy are all covered. Minor gaps exist—no direct store-deals listing (only a documented workaround) and no pagination for comments beyond local truncation—but agents can work around these.

    Maintenance

    ActivitySlowing
    ResponsivenessNo issues

    Resources