bruno-portfolio/agrobr-mcp
by Various
MCP server for Brazilian agricultural data — connect LLMs to 10 public data sources via agrobr
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_diariofuturos_b3estimativa_safraproducao_anualprogresso_safralistar_produtoshealth_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
Pairs with
Other entries in the index that connect to this one. Click through to see the chain.
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