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bruno-portfolio/agrobr-mcp

by Various

MCP server for Brazilian agricultural data — connect LLMs to 10 public data sources via agrobr

B

MCP

bruno-portfolio/agrobr-mcp

Added 1 June 2026

Overview

An MCP server that exposes Brazilian agricultural data from 10 public sources to LLMs. It uses the agrobr library to convert raw datasets into a structured interface compatible with the Model Context Protocol. Developers can query crop statistics, weather data, and government reports through this server.

Best for

Best for
Developers building LLM applications that need real-time or historical Brazilian agricultural data

Use cases

  • Query Brazilian crop yields and harvest data
  • Access public agricultural statistics from government APIs
  • Integrate farm-level data into LLM-based decision support tools

How to use

Install

pip install agrobr-mcp

Tools exposed

  • preco_diario
  • futuros_b3
  • estimativa_safra
  • producao_anual
  • progresso_safra
  • listar_produtos
  • health_check

Tested with

Claude Desktop, Claude Code, Cursor

Notes

An MCP server that exposes Brazilian agricultural data from 10 public sources to LLMs. It uses the agrobr library to convert raw datasets into a structured interface compatible with the Model Context Protocol. Developers can query crop statistics, weather data, and government reports through this server.

24 stars on GitHub. Last updated 2026-03-12. Licensed MIT.

Use cases

  • Query Brazilian crop yields and harvest data
  • Access public agricultural statistics from government APIs
  • Integrate farm-level data into LLM-based decision support tools

Pros

  • Open source and free to use
  • Unifies 10 disparate public data sources under one MCP interface
  • Simplifies LLM integration with Brazilian agricultural datasets

Cons

  • Limited to Brazilian agricultural data only
  • Small community (24 stars) and potentially less active maintenance
  • Requires familiarity with MCP and the agrobr library

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Open source and free to use
  • Unifies 10 disparate public data sources under one MCP interface
  • Simplifies LLM integration with Brazilian agricultural datasets

Cons

  • Limited to Brazilian agricultural data only
  • Small community (24 stars) and potentially less active maintenance
  • Requires familiarity with MCP and the agrobr library
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