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Simba MCP Server

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by getsimba-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

    A3.6/5.0

    Scored across 94 tools

    Disambiguation3/5

    Most tools have clearly distinct purposes and descriptions are unusually detailed, but several families overlap subtly: create_incrementality_test vs save_incrementality_test_design vs import_incrementality_tests vs design_incrementality_test, recipe/study authoring tools, and get_model_results vs the show_* chart wrappers. With 94 tools, an agent can still misselect within these clusters even though descriptions help.

    Naming Consistency5/5

    Tool names follow a consistent snake_case verb_noun pattern throughout (e.g. create_model, get_model_results, list_study_runs, run_optimizer), with only minor stylistic variants like show_* and diff_*. No camelCase or chaotic mixing is present.

    Tool Count1/5

    94 tools is far beyond a well-scoped set; even for a complex MMM platform this imposes a very large selection surface and constant risk of wrong-tool choice. The rubric treats 50+ tools as an extreme mismatch.

    Completeness5/5

    The surface covers the full lifecycle: data upload/pipelines, model creation, results, diagnostics, optimization, scenarios, studies/recipes/quality policies, campaign mapping, incrementality tests and designs, run history, projects and sharing. CRUD/lifecycle coverage is broad with very few obvious dead ends.

    Maintenance

    ActivityActive
    ResponsivenessUnresponsive

    Resources