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 recent community issues