How to Use the CVM Dados Abertos MCP in Google ADK

Q: How do I connect CVM Dados Abertos to Google ADK?

You initialize McpToolset using the StreamableHttpServerParameters pointing to your Vinkius endpoint. Pass this toolset instance to the LlmAgent constructor to expose the tools.

Q: Can I combine CVM Dados Abertos with BigQuery tools in Google ADK?

Yes, your agent can call getresource to find the data URL, fetch the file, and then write it to BigQuery. You simply include both the MCP toolset and your BigQuery tools in the agent's tool list.

Feed Brazilian capital markets data directly to your Google ADK enterprise agents with zero-config MCP tools.

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Connect CVM Dados Abertos MCP to Google ADK

Create your Vinkius account to connect CVM Dados Abertos to Google ADK 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 Google ADK

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Feed CVM Data into Google ADK Pipelines

This MCP Server exposes Brazilian investment fund metadata to your Gemini models using `list_datasets` and `search_datasets`. Your Google ADK agents call these tools to find financial tables, then pass the metadata directly into BigQuery for enterprise analysis. You configure the connection using the `McpToolset` class in your Python code. Gemini's million-token context window allows the agent to ingest large directory listings returned by the server without running out of memory.

Structure Corporate Data for BigQuery

The server retrieves specific resource schemas via `get_resource` and `get_dataset` to prepare financial data ingestion pipelines. Your Google ADK agent determines which datasets are relevant and structures the metadata for immediate import into Google Cloud storage. By restricting the tool list to just these retrieval functions, you prevent the agent from wandering into unrelated datasets. The agent focuses entirely on parsing the specific schema definitions returned by the CVM portal.

Map Brazilian Regulators with Vertex AI

This toolset queries regulatory structures through `list_groups` and `list_organizations` to map the Brazilian financial ecosystem. Your Gemini-powered agents use this organizational data to categorize filings before running predictive models in Vertex AI. The agent queries the CVM portal to find which department published a dataset, then updates your enterprise metadata catalog. This automates the classification of foreign financial sources inside your Google Cloud environment.

Setup guide

Set up CVM Dados Abertos MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with CVM Dados Abertos tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="CVM Dados Abertos_agent",
    model="gemini-2.0-flash",
    instruction="You have access to CVM Dados Abertos tools via MCP.",
    tools=mcp_tools,
)

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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 Google ADK

You initialize `McpToolset` using the `StreamableHttpServerParameters` pointing to your Vinkius endpoint. Pass this toolset instance to the `LlmAgent` constructor to expose the tools.

Yes, you can pass a list of allowed tool names to the toolset configuration. This prevents the agent from calling `list_organizations` if you only want it to use `search_datasets`.

Gemini's long-context window easily ingests the large metadata payloads returned by `get_dataset`. The MCP server responds with the raw resource definitions, which the agent parses in a single reasoning turn.

Yes, your agent can call `get_resource` to find the data URL, fetch the file, and then write it to BigQuery. You simply include both the MCP toolset and your BigQuery tools in the agent's tool list.

The server accesses only public Brazilian financial metadata, meaning no proprietary corporate data is exposed. Vinkius processes all requests in ephemeral V8 isolates, ensuring your query history is destroyed immediately after execution.

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