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Tuning Engines

by cerebrixos-org
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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

A3.7/5.0

Scored across 38 tools

Disambiguation5/5

Each tool targets a distinct resource and action (e.g., create_job vs. cancel_job, list_datasets vs. show_dataset). There is no overlap, and descriptions clearly differentiate related tools like estimate_job and create_job.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern in snake_case (e.g., list_models, export_model, cancel_evaluation). The naming is uniform and predictable, aiding agent selection.

Tool Count4/5

38 tools is on the higher side but appropriate for a comprehensive fine-tuning platform covering jobs, evaluations, datasets, models, marketplace, inference, and account management. The scope justifies the count.

Completeness5/5

The tool surface covers the full lifecycle: job creation, estimation, cancellation, retry, and monitoring; dataset and model CRUD; evaluation workflows; account management; marketplace; and inference. No obvious gaps exist.

Maintenance

ActivityMaintained
ResponsivenessNo issues

Resources