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Open Agent Search

Open Agent Search

by jayanth-mkv
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

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    TDQS

    A3.9/5.0

    Scored across 8 tools

    Disambiguation4/5

    Most tools are cleanly split by media type (web, books, images, videos, news) plus single vs. batch fetching, so boundaries are clear. The only real overlap is search_web versus search_everything, which both return text results, and an agent could plausibly pick the wrong one for a plain web query.

    Naming Consistency5/5

    All names are snake_case and follow a predictable verb-first pattern: search_<media> for queries and fetch_content / fetch_multiple_contents for retrieval. The singular/plural contrast on the fetch pair is deliberate and readable.

    Tool Count5/5

    Eight tools is well-scoped for a search-and-fetch server: five media-specific searches, one aggregate search, and two content fetchers. Each tool earns its place with no redundant entries.

    Completeness5/5

    The surface covers every common retrieval mode (text, books, images, videos, news, aggregate) plus single and parallel URL content extraction, with rich filters per media type and max_results up to 100 compensating for the lack of pagination. No obvious dead ends for a search-oriented domain.

    Maintenance

    ActivityMaintained
    ResponsivenessSyncing

    Resources