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ChatSpatial

by cafferychen777
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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

    B3.4/5.0

    Scored across 20 tools

    Disambiguation4/5

    Most tools target clearly distinct stages of spatial transcriptomics analysis, such as loading, preprocessing, embeddings, domain detection, deconvolution, and communication. A few pairs have overlapping scope—find_markers versus compare_conditions for differential expression, and analyze_spatial_statistics versus find_spatial_genes for spatial gene statistics—but descriptions and parameter differences help distinguish them.

    Naming Consistency5/5

    All tool names use snake_case and follow a verb_noun or verb_object convention (load_data, preprocess_data, find_markers, analyze_cnv, export_data). Verb choices vary appropriately by operation, with no inconsistent casing or mixed naming styles.

    Tool Count4/5

    The suite has 20 tools, slightly above the ideal 3-15 range, but this matches a comprehensive spatial transcriptomics workflow with many distinct analysis stages. Each tool earns its place, though the surface is somewhat heavy for an MCP server.

    Completeness4/5

    The tools cover the full analysis lifecycle: loading, preprocessing, embeddings, visualization, spatial statistics/domains/genes, deconvolution, annotation, cell communication, CNV, velocity, trajectory, and export/reload. Minor lifecycle gaps such as listing or deleting datasets prevent a perfect completeness score.

    Maintenance

    ActivityActive
    ResponsivenessResponsive

    Resources