How to Use the CVM Dados Abertos MCP in LangChain

Build complex reasoning chains using CVM Dados Abertos data directly within your LangChain pipelines.

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Connect CVM Dados Abertos MCP to LangChain

Create your Vinkius account to connect CVM Dados Abertos 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.

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Setup CVM Dados Abertos with LangChain

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Claude

Perplexity

Chain financial data in LangChain

Plug the CVM Dados Abertos toolset into your agent to turn raw registry data into structured reasoning steps. Your LangChain agent can call `list_organizations` to identify who published a report and then chain that into `search_datasets` to pinpoint specific filings. Every tool output flows naturally into the next link in your chain. You get full visibility into how your agent processes Brazilian market data using LangSmith tracing.

Automated market research workflows

Construct multi-step pipelines that fetch metadata through `get_dataset` for deeper analysis. Your agent decides the exact order of operations, moving from broad queries to specific resource extraction without manual intervention. This setup removes the need for custom scrapers. You write the logic, and the agent handles the heavy lifting of navigating the CVM portal's structure.

Contextual financial modeling

Feed live financial data into vector stores or databases within your LangChain agent. By using `list_groups` first, you filter the noise and focus the agent's attention on specific segments like investment funds or companies. Keep your agent stateful by using client sessions. This ensures that multi-turn conversations stay grounded in the specific CVM records you fetched during the initial steps.

Setup guide

Set up CVM Dados Abertos MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
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 LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "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 CVM Dados Abertos tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "cvm-dados-abertos-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 CVM Dados Abertos transactions"
    })
    print(result["messages"][-1].content)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by CVM Dados Abertos. 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 CVM Dados Abertos MCP in LangChain

Install the necessary adapters and initialize the server using the provided URL. Pass the tools fetched from the server directly into your agent constructor to start executing.

Absolutely. Since every tool output acts as a valid input for subsequent nodes, you can build sophisticated agents that reason over raw CVM data.

Yes. You can aggregate this server with others in your LangChain environment to combine CVM datasets with internal databases or external APIs.

Your connection uses an ephemeral V8 sandbox. We only touch public Brazilian capital markets data, so no sensitive financial records or PII are ever processed.

Yes. Every interaction is logged through LangSmith, giving you a clear view of latency and token usage for every request made to the CVM portal.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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