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eduardoabreu81

Forge Neo MCP

by eduardoabreu81
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Python
Hybrid

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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

    A3.9/5.0

    Scored across 10 tools

    Disambiguation4/5

    Tools are mostly distinct by resource and action—LoRA search vs detail, module check vs download, generation vs progress—but model_profile and prompt_dialect overlap on prompt dialect, and models/model_profile could be confused at a glance. The detailed descriptions mitigate most ambiguity.

    Naming Consistency4/5

    Names consistently use lowercase snake_case and a readable resource-oriented style (loras, lora_info, models, module_check). Not all are verb_noun—generate is a bare verb and progress is ambiguous—so it is not a perfect 5, but there is no chaotic convention mixing.

    Tool Count5/5

    Ten tools is well within the ideal 3–15 range and matches the server's scope: discovery, model/prompt/LoRA/module setup, generation, and progress control. No tool feels redundant or superfluous.

    Completeness4/5

    The surface covers the full generation workflow—model loading, profiling, prompt dialect, LoRA lookup, module diagnostics/download, generate, and progress monitoring. Minor gaps exist (no LoRA download/management, no explicit output/history listing), but they are not required for the core purpose.

    Maintenance

    ActivitySlowing
    ResponsivenessNo issues

    Resources