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Kiln

by codeofaxel
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Python

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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

B3.1/5.0

Scored across 468 tools

Disambiguation1/5

With 468 tools, the surface is riddled with strings of near-identical tools that do the same thing: get_material_info/get_material_properties/get_material_design_profile (and several more material lookups), plus a range of analyze/diagnose/check print-issue, mesh-analysis, and failure-recovery tools. Even with detailed descriptions, an agent cannot reliably select between them, especially when tools with the same behavior are named differently.

Naming Consistency3/5

Tool names are uniformly snake_case, but no consistent verb-first pattern emerges. Many use noun-first conventions (printer_status, job_status, queue_summary) while others use verb_* (list, get, check, validate, analyze, monitor, watch, run), and there are contradictory subtleties such as multiple merge commands (merge_stl, merge_mesh_files, compose_models, merge_multicolor_gcode). There is no mixed casing or random names, but the vocabulary is broad and overlapping.

Tool Count1/5

468 tools is far beyond the 3-15 well-scoped range; even for a comprehensive 3D-printing server, this is extreme over-provisioning. Such a large count inflates the model's context, yields massive overlaps, and makes the set far more difficult to navigate than a compact, curated tool set.

Completeness4/5

The surface is incredibly broad: full print lifecycle, slicing, mesh analysis, generation, material management, fleet, marketplaces, fulfillment, cost, recovery, security, enterprise, and team tools. There are minor gaps (e.g., no printer deletion/rename, no generic update for shipping profiles, and some deprecated aliases are honored) but almost every domain has a viable workflow path from start to finish.

Maintenance

ActivityActive
ResponsivenessSlow

Resources