How to Use the BCB Câmbio — Dólar PTAX, Euro e 150+ Moedas MCP in LangChain
Pipe official Brazilian exchange rates directly into LangChain workflows for automated financial pipelines.
Works with every AI agent you already use
…and any MCP-compatible client
Connect BCB Câmbio — Dólar PTAX, Euro e 150+ Moedas MCP to LangChain
Create your Vinkius account to connect BCB Câmbio — Dólar PTAX, Euro e 150+ Moedas to LangChain and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Chain FX Conversions in LangChain
Your ReAct agent needs to convert a European invoice to Brazilian Reais. It calls `listar_moedas` to verify the EUR code exists in the Central Bank catalog. Then it pulls the exact buy and sell rates for the invoice date using `get_cotacao_moeda`. The output of that MCP Server call becomes the input for your next chain step. You calculate the final settlement amount and push it to your accounting database. LangSmith tracks the exact token usage and latency for every API request.
Build Financial Pipelines with PTAX Data
Hardcoding exchange rates breaks financial models. You establish this MCP connection so your LangChain agents pull official historical data using `get_dolar_periodo`. The agent requests up to a year of PTAX dollar quotes formatted as MM-DD-YYYY. For longer historical trends, the agent switches to `get_dolar_sgs`. It grabs series 1 for buy rates and 10813 for sell rates. The pipeline feeds those arrays directly into a Python REPL tool to generate volatility charts.
Automate Daily BRL/USD Settlements
Brazilian trade operations rely on the official PTAX reference rate. Your LangGraph state machine triggers a daily task that runs `get_cotacao_dolar` to fetch the central bank's official buy and sell values. Because LangChain handles the tool routing automatically, the agent decides if it needs the closing bulletin or just the intermediate rates. It extracts the exact float values and formats a settlement report without human intervention.
Set up BCB Câmbio — Dólar PTAX, Euro e 150+ Moedas MCP in LangChain
Prerequisites
- Python 3.10+ installed
-
langchain-mcp-adapters+langgraphpackages - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Run
pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChainBaseToolobjects. - 2
Connect via HTTP transport
Use
MultiServerMCPClientwith"transport": "http"pointing to your Vinkius endpoint. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. - 3
Create a ReAct agent
Pass the discovered tools to
create_react_agent()from LangGraph. The agent automatically routes BCB Câmbio — Dólar PTAX, Euro e 150+ Moedas tool calls through the MCP protocol. - 4
Run with any LLM
Swap
ChatOpenAIforChatAnthropic,ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.
from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI
async with MultiServerMCPClient({
"bcb-cambio-dolar-ptax-euro-e-150-moedas-mcp": {
"transport": "http",
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
}
}) as client:
tools = client.get_tools()
agent = create_react_agent(
ChatOpenAI(model="gpt-4o"),
tools,
)
result = await agent.ainvoke({
"messages": "List recent BCB Câmbio — Dólar PTAX, Euro e 150+ Moedas transactions"
})
print(result["messages"][-1].content) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Banco Central do Brasil. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Common questions about BCB Câmbio — Dólar PTAX, Euro e 150+ Moedas MCP in LangChain
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