How to Use the BCB Juros — Selic, CDI e Expectativas Focus MCP in Pydantic AI

Get type-safe Brazilian Selic and CDI rates directly in Pydantic AI with strict runtime validation.

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Connect BCB Juros — Selic, CDI e Expectativas Focus MCP to Pydantic AI

Create your Vinkius account to connect BCB Juros — Selic, CDI e Expectativas Focus to Pydantic AI 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 BCB Juros — Selic, CDI e Expectativas Focus with Pydantic AI

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Type-safe Brazilian rate validation in Pydantic AI

Your agent uses `get_selic_meta` to pull the COPOM target rate with strict schema validation before any code executes. This MCP Server integration ensures your financial models never ingest malformed data. If the Central Bank of Brazil's API returns an unexpected format, the framework fails loudly and immediately. This strict validation prevents silent corruption in your downstream portfolio calculations and automated reports.

Parse complex Focus Survey projections safely

Fetch and validate institutional market forecasts using `get_expectativas_selic`. The tool returns the median, mean, and range of Selic projections, which are instantly mapped to typed Python objects. The MCP Server ensures that your pricing models receive clean data, making it easy to write reliable financial pipelines. You can confidently pass these validated Focus expectations to your models, knowing every float and string matches your exact specifications.

Compare CDI and daily Selic rates reliably

Pull daily interbank metrics by calling `get_cdi` and `get_selic_diaria` within a unified toolset. Pydantic AI handles the execution, verifying that SGS Series 11 and 12 data structures are perfectly formed. By enforcing strict runtime types on daily effective rates, you eliminate the risk of parsing errors. Your automated trading or risk management systems can rely on clean, validated interest rate data every single day.

Setup guide

Set up BCB Juros — Selic, CDI e Expectativas Focus MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "bcb-juros-selic-cdi-e-expectativas-focus-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to BCB Juros — Selic, CDI e Expectativas Focus tools.",
)

result = await agent.run("List recent BCB Juros — Selic, CDI e Expectativas Focus transactions")
print(result.output)

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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 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 Juros — Selic, CDI e Expectativas Focus MCP in Pydantic AI

Install the MCP extension and instantiate MCPToolset with the server's HTTP URL. Pass this toolset to your agent to grant it type-safe access to tools like get_cdi and get_selic_meta.

The framework will raise a validation error at runtime. This prevents your agent from making decisions based on corrupted or partial interest rate data, protecting your financial applications.

Yes, the server is model-agnostic. Your Pydantic AI agent can use these tools to fetch get_selic_diaria whether it is powered by OpenAI, Anthropic, or a local LLM.

Yes, the server integrates with the MCP Server's async workflows. Your application can fetch get_expectativas_selic concurrently without blocking your main application loop.

The server operates in a zero-trust environment and only handles public macroeconomic indicators. No private financial schemas, API keys, or proprietary variables are ever stored or transmitted outside your local runtime.

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