mcp-brasil is Trending — Here's How to Add AI Image Generation to Brazilian APIs
mcp-brasil just exploded on GitHub with 373+ stars in days. It exposes 28 Brazilian public APIs — IBGE, Banco Central, TSE, DataJud, INPE, BrasilAPI, and more — directly to AI assistants via the Model Context Protocol (MCP).
Brazilian developers are using it to ask Claude and GPT questions like:
- "Quais os 10 maiores contratos do governo federal em 2024?"
- "Qual a tendência da taxa Selic nos últimos 12 meses?"
But there's a gap: mcp-brasil reads data, but can't generate content. What if you could also generate images, speak Portuguese via TTS, or create videos from that data?
That's what this tutorial covers.
What Is MCP?
MCP (Model Context Protocol) is Anthropic's open protocol for connecting AI assistants to external tools. mcp-brasil implements it for 28 Brazilian government APIs with 213 tools, smart BM25 discovery, and batch execution.
pip install mcp-brasil
The Missing Piece: NexaAPI
NexaAPI is a unified AI inference API — 50+ models, OpenAI-compatible, at $0.003/image (5x cheaper than alternatives).
Available on RapidAPI: rapidapi.com/user/nexaquency
Python Tutorial: IBGE Data + AI Image Generation
# pip install nexaapi requests
from nexaapi import NexaAPI
import requests
client = NexaAPI(api_key='YOUR_RAPIDAPI_KEY')
# Fetch city data from IBGE (mcp-brasil pattern)
def get_city_info(city_code):
url = f'https://servicodados.ibge.gov.br/api/v1/localidades/municipios/{city_code}'
return requests.get(url).json()
# Generate AI image — $0.003/image!
def generate_city_image(city_name):
result = client.image.generate(
model='flux-schnell',
prompt=f'Beautiful aerial view of {city_name}, Brazil, photorealistic, vibrant colors',
width=1024,
height=1024
)
return result.image_url
# Generate Portuguese TTS
def generate_portuguese_tts(text):
result = client.audio.tts(
text=text,
voice='pt-BR-female',
model='tts-multilingual'
)
return result.audio_url
# Combined workflow
city = get_city_info(3550308) # São Paulo
image_url = generate_city_image(city['nome'])
print(f"✅ City image: {image_url}") # Cost: $0.003
tts_url = generate_portuguese_tts(f"Bem-vindo a {city['nome']}!")
print(f"✅ Portuguese TTS: {tts_url}")
JavaScript Tutorial: CNPJ Lookup + Company Image
// npm install nexaapi axios
import NexaAPI from 'nexaapi';
import axios from 'axios';
const client = new NexaAPI({ apiKey: 'YOUR_RAPIDAPI_KEY' });
async function getCNPJInfo(cnpj) {
const { data } = await axios.get(`https://brasilapi.com.br/api/cnpj/v1/${cnpj}`);
return data;
}
async function generateCompanyImage(companyName) {
const result = await client.image.generate({
model: 'flux-schnell',
prompt: `Professional headquarters of ${companyName} in Brazil, modern architecture`,
width: 1024,
height: 768
});
return result.imageUrl; // Only $0.003!
}
// Run it
const company = await getCNPJInfo('33000167000101');
const imageUrl = await generateCompanyImage(company.razao_social);
console.log(`Generated: ${imageUrl}`);
Pricing Comparison
| Provider | Image | TTS |
|---|---|---|
| NexaAPI | $0.003 | $0.015/1K chars |
| OpenAI DALL-E 3 | $0.04 | $0.015/1K |
| Stability AI | $0.02 | N/A |
| ElevenLabs | N/A | $0.30/1K |
NexaAPI is 10x cheaper for images.
Use Cases
- 🏙️ City Tourism: IBGE data → photorealistic city images
- 🏢 Company Intelligence: CNPJ lookup → company visualization
- 🗳️ Electoral Analysis: TSE data → infographics + Portuguese TTS
- 🌿 Environmental: INPE fire data → visual reports
Resources
- 🔗 mcp-brasil: github.com/jxnxts/mcp-brasil
- 🚀 NexaAPI: nexa-api.com
- 🔑 Free API Key: rapidapi.com/user/nexaquency
- 🐍 Python SDK:
pip install nexaapi→ pypi.org/project/nexaapi - 📦 Node SDK:
npm install nexaapi→ npmjs.com/package/nexaapi
Have you used mcp-brasil in your projects? What Brazilian APIs are you most excited about? Drop a comment below! 🇧🇷
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