fm-mcp
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ToolPiperofficial
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TDQS
Scored across 4 tools
Each tool targets a clearly distinct operation: classify (pick from given labels), extract (schema-bound fields), ocr (read text from images), and summarise (condense prose). There is no overlap in verb, input type, or output shape, and each description even states what it is NOT for. An agent can select unambiguously.
Three tools are lowercase verbs (classify, extract, summarise) in a consistent style with no noun collisions. The single deviation is 'ocr', an acronym/process name rather than a verb, but it is a standard, unambiguous term and the overall set still reads as a predictable pattern.
Four tools is well-scoped for a focused on-device text-processing server. Each tool covers a genuinely different capability (classification, extraction, OCR, summarisation) and none feels redundant or extraneous.
The surface covers the main on-device operations: classify, extract, ocr, and summarise, with clear input/output behavior for each. Minor gaps exist, such as no explicit translation, Q&A, or generic generation tool, but the core text-processing lifecycle is well covered and workable.