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KumoRFM MCP Server

Official
by kumo-ai
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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

    A4.2/5.0

    Scored across 12 tools

    Disambiguation5/5

    Every tool addresses a distinct aspect of the workflow: authentication, file discovery, metadata inspection/update, graph materialization, prediction, evaluation, explanation, and documentation. There is no functional overlap that would cause confusion.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern in snake_case (e.g., authenticate, find_table_files, inspect_graph_metadata). This makes the expected action and target clear and predictable.

    Tool Count5/5

    12 tools cover the necessary stages of the KumoRFM pipeline without being excessive. Each tool earns its place, and the count is well-suited for a domain-specific ML server.

    Completeness5/5

    The tool set provides end-to-end coverage: data discovery, graph setup, materialization, prediction, evaluation, and explanation. Supporting tools like get_docs and get_mermaid enhance usability. No critical gaps are evident.

    Maintenance

    ActivityInactive
    ResponsivenessUnresponsive

    Resources