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agrobr-mcp

by bruno-portfolio
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Python
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    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A3.7/5.0

    Scored across 14 tools

    Disambiguation4/5

    Each tool targets a distinct dataset (spot prices, futures, exports, crop estimates, livestock, deforestation, fires, climate) and descriptions clarify the resource. Some crop-production tools overlap conceptually (estimativa_safra, producao_anual, serie_historica_safra, progresso_safra, balanco), but their data granularity differs and descriptions help distinguish them.

    Naming Consistency4/5

    All tool names use snake_case, mostly Portuguese noun phrases, giving a predictable pattern. Minor deviations exist: health_check is English and listar_produtos uses a verb while most others are nouns, but the set remains largely consistent.

    Tool Count5/5

    14 tools for a broad Brazilian agricultural data API is well-scoped within the ideal 3–15 range. Each tool maps to a distinct data domain (prices, crops, livestock, environment, metadata), with no obvious redundancy or trivial padding.

    Completeness4/5

    The surface covers prices, futures, exports, crop estimates/production/history/progress, supply-demand balance, livestock, deforestation, fire, and climate, plus discovery and health checks. Minor gaps such as import data or finer sub-state granularity remain, but core workflows are well covered.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources