local-llm-mcp
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TDQS
Scored across 3 tools
Each tool has a clearly distinct purpose: listing models, asking a model a prompt, and classifying text into labels. There is no overlap between querying for answers and categorizing input, and the model-listing tool is unambiguously separate from both.
All three tools follow a consistent local_ prefix with clear verb_verb-noun style (models, ask, classify). The pattern is uniform and predictable, making selection straightforward.
At three tools, this is on the low end but each earns its place for a focused local-LLM utility server. The count is appropriate for the narrow scope of running local model inference, though it borders on thin.
The server covers the core lifecycle for local model interaction: discovery (local_models), free-form prompting (local_ask), and structured classification (local_classify). A minor gap is the lack of a tool to pull or manage models, but for the stated inference-focused purpose the surface is largely complete.