F
licenseA
qualityD
maintenanceRoutes narrow text-processing tools (classification, extraction, summarization, etc.) to budget models to reduce token consumption on the main model.
7
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ai-workers-mcp
by basttran
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TDQS
A3.9/5.0
Scored across 12 tools
Disambiguation5/5
Each tool has a clearly distinct purpose: bullet points, classification, comparison, email drafting, field extraction, free generation, outlining, proofreading, Q&A, rewriting, summarization, and translation. Overlap is minimal and descriptions effectively disambiguate.
Naming Consistency4/5
All tools follow an ai_verb pattern (e.g., ai_bullet, ai_classify). The outlier is ai_email_draft, which uses a noun+verb combination, but the pattern is otherwise consistent.
Tool Count5/5
With 12 tools, the set is well-scoped for a general-purpose LLM text processing server. It covers a broad range of common tasks without being overwhelming.
Completeness4/5
The tools cover most common text operations (generate, summarize, classify, translate, etc.). Minor gaps exist (e.g., sentiment analysis, grammar checking), but the core functionality is solid.
Maintenance
ActivityInactive
ResponsivenessNo issues