Repository profile
jxnxts/mcp-brasil
MCP Server para 41 APIs públicas brasileiras
Why this page exists
Use this profile to move from awareness into adoption-oriented inspection.
Best next step
Check the summary, then compare it against similar projects before touching production.
Research posture
Momentum helps discovery. Fit, maintenance quality, and reversibility decide adoption.
Editorial summary
mcp-brasil is a comprehensive MCP server designed to connect AI agents to 41 public APIs from Brazil, covering diverse areas such as economy, legislation, transparency, judiciary, elections, environment, health, and public safety. With 326 tools at your disposal, this project enables users to access and analyze governmental data seamlessly. Notably, 38 of these APIs do not require an API key, making it easy for users to get started quickly, while three others offer free keys for enhanced functionalities. The server supports advanced features like cross-referencing multiple APIs for combined insights and batch execution of queries for efficient data retrieval.
Adoption analysis
Best-fit use case
jxnxts/mcp-brasil is most useful to evaluate when your team is researching AI and developer automation. Compare its documented workflow with your runtime, deployment model, and maintenance capacity before adopting it.
Momentum signal
Recent tracked star growth is modest, so maintenance quality and fit may matter more than momentum. Daily and three-day changes are discovery signals, while total stars show accumulated awareness.
Adoption caution
Before adding it to production, review license terms, dependency footprint, security guidance, open issue quality, and whether there is a clear path to migrate away later.
What to inspect next
- 1Look for a documented installation or setup path before using the project.
- 2Compare its topic focus (ai-agents, apis-publicas, brazil, claude) with the problem your team is actually solving.
- 3Identify at least two alternatives so the decision is not based on one ranking page.
- 4Read recent issues and releases to understand maintenance rhythm, breaking changes, and common failure modes.