PyScrappy
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TDQS
Scored across 24 tools
Most tools are clearly separated by target source or data type, so an agent can usually pick the right one from the name alone. The main ambiguity is that scrape_with is a generic dispatch that can overlap with the specialized scrapers, and a few search/scrape pairs (e.g. search_ubereats vs scrape_zomato) serve similar purposes but descriptions disambiguate them.
Names follow readable snake_case verb_noun structure, but the verbs are mixed across three patterns: search_*, scrape_*, and get_* with occasional one-offs like lookup_movie, define_word, and scrape_with. This is consistent within clusters but not predictable across the whole toolset.
At 24 tools, the set is in the heavy range and feels like a broad aggregation of scrapers rather than a tightly scoped server. The count is defensible for a multi-site scraping toolkit, but it is large enough that navigation and selection become a real burden.
The server covers the core scraper lifecycle well: generic URL scraping, named-source scrapers, plugin discovery, and generic dispatch via scrape_with. Minor gaps exist, such as no runtime scraper registration and no detailed arg discovery for registered plugin scrapers, but the main workflows are functional.