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VisoMaster MCP

VisoMaster MCP

by jrajasekera
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Python
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    TDQS

    A3.9/5.0

    Scored across 14 tools

    Disambiguation4/5

    Each tool targets a distinct stage of the media pipeline (upload → detect → swap → artifact) or a distinct job-lifecycle action, and the descriptions actively disambiguate near-neighbours like list_jobs vs job_status and view_artifact vs download_artifact. The only real friction is the three-way cleanup surface (cancel_job / delete_job / prune_storage), where an agent must reason about job state and age to pick correctly.

    Naming Consistency4/5

    Nearly all names are snake_case verb_noun (upload_media, detect_faces, submit_swap, normalize_media, cancel_job, delete_job, prune_storage). Two exceptions — health_check and job_status — invert into noun_verb/noun_noun, but they remain readable and unambiguous.

    Tool Count5/5

    14 tools is well inside the healthy range and each one earns its place: one entry point per pipeline stage plus a small, coherent job-control and storage-maintenance set. Nothing feels padded or missing at the count level.

    Completeness4/5

    Coverage is strong for the stated domain: media ingestion and inspection, face detection with identity grouping, preview and full render submission, normalization, full job lifecycle (submit/list/status/cancel/delete), and artifact viewing/downloading. Minor gaps remain — there is no per-file upload listing or deletion (only age-based prune_storage), no way to manage or persist face mappings across sessions, and no standalone job-log or artifact-listing operation outside job_status.

    Maintenance

    ActivityMaintained
    ResponsivenessNo recent community issues

    Resources