A
licenseNot graded
qualityF
maintenanceEnables PDF document processing including text, image, and table extraction, as well as intelligent classification and similarity analysis across multiple languages.
50
MIT
Text Classification MCP Server (Model2Vec)
by baobab-tech
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TDQS
A3.6/5.0
Scored across 6 tools
Disambiguation5/5
Each tool has a distinct purpose: adding categories (single/batch), classifying text (single/batch), listing, and removing categories. No overlap or ambiguity.
Naming Consistency5/5
All tools use snake_case and follow a consistent verb_noun pattern (e.g., add_custom_category, batch_classify, list_categories). No mixing of styles.
Tool Count5/5
Six tools is well-scoped for a text classification server: category CRUD (add/batch add, list, remove) and classification (single/batch). Neither too few nor too many.
Completeness4/5
Covers core functionality: category management and classification. Missing an update category tool is a minor gap, but agents can work around it by removing and re-adding.
Maintenance
ActivityInactive
ResponsivenessNo issues