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persistmcp

AIm

by persistmcp
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Python
Remote

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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 20 tools

Disambiguation5/5

Each tool targets a distinct resource/action: logging vs reading vs updating sessions, body metrics, exercises, programs, goals, and coaching context. Close neighbors like search_exercise_pool vs list_exercises and get_stats vs get_coaching_context are explicitly differentiated in their descriptions.

Naming Consistency5/5

Tool names follow a consistent verb-first snake_case convention: log_*, get_*, update_*, upsert_*. Exceptions like import_document, review_program_draft, and search_exercise_pool still follow the verb_noun pattern and do not break the overall consistency.

Tool Count4/5

20 tools is above the typical lean range, but the coaching/training domain is broad—covering sessions, body metrics, exercises, programs, goals, coaching context, and stats—and each tool has a distinct job. It is slightly heavy but not bloated.

Completeness4/5

Core workflows are covered: log/read/update/delete sessions, log/read body metrics, create/search/list exercises, get/create programs, manage goals and coach profile, plus stats and import/review. Minor gaps exist (no delete for body metrics, no read-back for coaching events, no dedicated single-exercise fetch), but agents can work around them.

Maintenance

ActivityActive
ResponsivenessNo issues

Resources