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just-prs-mcp

just-prs-mcp

by dna-seq
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Python
Hybrid

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    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

    A4.1/5.0

    Scored across 20 tools

    Disambiguation4/5

    Most tools target a distinct action-resource pair: search, info, compute, post-process, report, and job handling are clearly separated. The main ambiguity is between compute_prs_batch and compute_prs_by_trait, which both handle multiple scores, though their descriptions clarify the one-genome-vs-many-genomes distinction.

    Naming Consistency4/5

    The majority of tools follow a snake_case verb_noun pattern (compute_prs, list_genomes, build_prs_prompt, compare_genomes). A few noun-style names (best_performance, vcf_metainfo, percentile, absolute_risk, score_info, trait_info) break the pattern, but the overall convention remains predictable.

    Tool Count3/5

    At 20 tools, this is on the heavy side and spans a very wide pipeline from catalog search to VCF normalization to reporting. The count is defensible for the domain, but some tools like percentile, absolute_risk, and assess_quality are narrowly scoped and could conceivably be folded into compute/interpretation results.

    Completeness5/5

    The tool surface covers the full PRS lifecycle: discovery, input preparation, computation, interpretation, comparison, reporting, and async job recovery. There are no obvious dead ends — job IDs feed prs_job_status, result paths feed compare_genomes/build_prs_prompt/plot_trait_panel, and computed z-scores feed absolute_risk.

    Maintenance

    ActivityInactive
    ResponsivenessNo recent community issues

    Resources