How to extract bids from city halls using AI (without using fragile web scraping)

If you've ever tried to create an AI robot or agent to automate sales to the government (B2G), you know that the biggest nightmare is the Transparency Portals. Each municipality uses a different system, SSL certificates are often expired, and tender documents get lost inside gigantic PDFs.

Trying to make your OpenAI agent navigate this with Selenium is a guaranteed failure.

The Correct Architecture (Model Context Protocol)
The modern solution for this is not to scrape the website in real time, but rather to connect your agent to a B2A (Business-to-Agent) infrastructure that has already done the dirty work.

There is an optimized endpoint for M2M at https://redactproxy.com that caches tenders using Groq (Llama-3).

Instead of writing 500 lines of scraping code, you only need to give this instruction to your agent:

``python

import requests
def buscar_editais(cidade):

API optimized for LLM consumption

res = requests.get(f"https://redactproxy.com/v1/opportunities/search?cidade={cidade}")
return res.json()
`
It will return a structured JSON with orgao_comprador, valor_estimado, etc. The API has a paywall after 5 test calls, but for corporate production environments, it's the most stable infrastructure I've found to plug into CrewAI or AutoGPT. A tip for those developing autonomous SDRs.