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TensorFeed MCP Server

by RipperMercs
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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 24 tools

    Disambiguation4/5

    Most tools have clearly distinct purposes, like account_status for credit balance, benchmark_series for historical scores, and route_verdict for model routing. However, get_ai_status and is_service_down both check provider status, though with different depth, causing slight ambiguity.

    Naming Consistency2/5

    Tool names follow no consistent pattern: some use snake_case (account_status), some verb_noun (get_ai_news), some noun_verb (is_service_down), and some are compound names (failover_verdict, provider_deepdive). This variety reduces predictability.

    Tool Count4/5

    With 24 tools, the server covers a wide domain of AI ecosystem data and verdicts. The count is high but justified by the breadth of functionality; it is not excessive given the scope.

    Completeness5/5

    The tool set comprehensively covers pricing, status, benchmarks, various verdicts, news, webhooks, SSVC, stack safety, and x402 settlements. No obvious missing operations for the server's purpose.

    Maintenance

    ActivityMaintained
    ResponsivenessUnresponsive

    Resources