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bruno-portfolio

agrobr-mcp

by bruno-portfolio
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Python
Remote

exportacao

Brazilian agricultural exports summed by month (Comex Stat; ABIOVE fallback).

Instructions

Brazilian agricultural exports summed by month (Comex Stat; ABIOVE fallback).

    Products: soja, milho, cafe, algodao, acucar, farelo_soja, oleo_soja.
    The Comex Stat query can take about a minute.

    Args:
        produto: Product (e.g. "soja", "farelo_soja")
        ano: Year (default: current year)
        uf: State of origin (e.g. "MT"). Empty = Brazil.

Input Schema

NameRequiredDescriptionDefault
ufNo
anoNo
produtoYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.2.0

TDQS

B3.4/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full behavioral burden and partially meets it: it discloses the data-source fallback chain (Comex Stat with ABIOVE fallback) and a latency warning of roughly one minute. It says nothing about permissions, rate limits, or whether results are cached, and never explicitly frames the operation as a read-only query.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose is front-loaded in the first line, followed by a compact product list, a latency note, and three short arg lines. The docstring-style 'Args:' block is slightly formal overhead but nothing is padded or redundant.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return structure needn't be described. Combined with the product enumeration, geography semantics, source fallback, and latency caveat, an agent has enough to invoke this correctly; only the ano default discrepancy leaves a small ambiguity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate and largely does: it enumerates the seven valid produto values, gives the 'MT' style for uf, and explains that empty uf means all of Brazil. The only weak spot is ano, where it says 'default: current year' while the schema default is 0.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific resource and transformation: 'Brazilian agricultural exports summed by month', plus the upstream sources (Comex Stat, ABIOVE fallback). An agent can distinguish it from producao_anual or preco_diario by the export/monthly framing, though it never names a sibling explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No when-to-use, when-not-to-use, or alternative routing is given. The product list defines scope implicitly, but an agent gets no help deciding between this and the production, balance, or price tools in the sibling set.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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