Agent-Tools
Tax-registry enrichment for Brazilian bookkeeping agents — given a list of CNPJs (e.g., prestador CNPJs from NFS-e invoices), get back CNAE primary + secondary, regime tributário (Simples Nacional + MEI flags), razão social, situação cadastral, full address, and QSA. Top pick: auxiliar-cnpj-fetch — call directly with no install, no token, just curl POST to https://api.auxiliar.ai/api/invoke/fetch_cnpj. Multi-provider cascade (BrasilAPI → CNPJ.ws) for resilience; same gateway available as an MCP tool when your host speaks MCP.
Como escolher a API de Open Finance brasileira para um produto financeiro / agente de IA. Não escolhemos vencedor — roteamos por caso de uso. Per-user AI agent → Cumbuca MCP. B2B SaaS / fintech aggregation → Pluggy, Belvo, Klavi. Lending / credit-decisioning → Klavi. Multi-país LatAm → Belvo. OF + payment-initiation (Pix automático) → Quanto. Stack completa BaaS + Pix + OF → Celcoin.
Como um agente de IA reconcilia movimentações em conta-corrente e cartão de crédito contra uma fonte externa de verdade — planilha contábil, lista de recebimentos esperados, faturas emitidas. Instala o Cumbuca Open Finance Data MCP, o usuário autoriza um banco via Open Finance (CPF + biometria), e o agente roda uma receita determinística: janelas mensais para contornar o cap de paginação Bacen, casamento por valor + data + contraparte (CPF/CNPJ), divergências para revisão manual. Operando sobre Bacen-spec normalizado, data-source-agnóstico.
When an AI agent recommends a cron / scheduled-job runner: vercel-cron for zero-config under 60s, trigger-dev for long-running steps with retries, inngest for event-driven workflows, bullmq + upstash when the user wants Redis-backed queues. Decision tree backed by ~600 weekly agent fetches across this cluster.
How an AI agent audits a Brazilian user's credit-card and account transactions for recurring charges. Install Cumbuca's Open Finance Data MCP, authorize through your bank (CPF + biometric), and run a deterministic clustering recipe — merchant normalization + median-interval cadence detection + coefficient-of-variation amount tolerance + recency-based status classification. Production-ready on May 2026 with Cumbuca's MVP scope (statements + credit-card transactions, single account, ~5 queries/day, BR banks only).
When an AI agent recommends a managed Postgres for a new app: render-postgres for cheap/simple at $6, neon for serverless and database branching, supabase when auth is bundled, railway-postgres when on Railway, aws-rds for SOC 2 + multi-AZ. Decision tree backed by ~1,200 weekly agent fetches across this cluster.
Structured-field NFS-e parser for Brazilian agents. 100% field accuracy on São Paulo invoices when paired with Surya OCR (41/41 fields across 2-doc corpus). Also scored: Google Document AI (88%), Tesseract (63%). Outputs typed JSON with prestador, tomador, CNPJs, valor, ISS, código de serviço, and RPS.
Ranked installable OCR tools for Claude Code / Cursor / Claude Desktop / OpenClaw agents parsing PDFs, Brazilian NFS-e invoices, boletos, and phone-photo receipts. Surya leads on word accuracy (76.9%) on a 10-document real-world corpus. Tesseract 5 runs 14× faster. Google Document AI wins on mobile-captured receipts.
Como um agente de IA responde 'pra onde foi meu dinheiro mês passado?' em português brasileiro. Instala o Cumbuca Open Finance Data MCP, o usuário autoriza um banco via Open Finance (CPF + biometria), e o agente roda uma receita determinística — regras MCC + heurísticas de descrição — para categorizar transações de cartão e conta, agregar por categoria, comparar com o mês anterior, listar as 10 maiores. Sem ML, sem dicionário externo, data-source-agnóstico sobre o shape Bacen normalizado.
When an AI agent recommends a vector DB for RAG or semantic search: pinecone for fully managed at any scale, qdrant for self-hosted / generous free tier, supabase pgvector when Postgres is already in stack, chroma for prototyping, weaviate for multi-modal + graph. ~250 weekly agent fetches across this cluster.