How to Use the BEA (Bureau of Economic Analysis) MCP in Pydantic AI

Q: How do I add the BEA (Bureau of Economic Analysis) tools to my Pydantic AI project?

Make sure you have pydantic-ai-slimmcp installed. Then instantiate an MCPToolset with your Vinkius server URL and add it to your agent's toolsets list. That's it.

Q: How does Pydantic AI help when getting GDP data from the BEA (Bureau of Economic Analysis)?

When your agent calls getdata for GDP figures, Pydantic AI will validate the response against a Pydantic model you define. If the data doesn't match the expected structure, like a number coming back as a string, it will throw an error, protecting your application from bad data.

Q: Can a Pydantic AI agent discover available years for a BEA (Bureau of Economic Analysis) dataset?

Yes. Your agent would first use getparameterlist to confirm 'Year' is a valid parameter for the dataset. Then, it would call getparametervalues on the 'Year' parameter to get a list of all available years directly from the BEA.

Get type-safe, validated US economic data from the BEA directly into your Pydantic AI agent. No more silent data corruption.

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Connect BEA (Bureau of Economic Analysis) MCP to Pydantic AI

Create your Vinkius account to connect BEA (Bureau of Economic Analysis) 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 BEA (Bureau of Economic Analysis) with Pydantic AI

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Perplexity

Stop Guessing API Schemas

This MCP Server provides four tools to query the Bureau of Economic Analysis. The key tools, `get_parameter_list` and `get_parameter_values`, let your agent discover the exact requirements for a data request before you make it. This is a perfect match for Pydantic AI. You can build Pydantic models for your requests based on the discovery tools, ensuring your agent always sends a valid query to the `get_data` tool. It's about building agents that don't fail because of a typo in a parameter name.

Fail Loudly with Pydantic AI Validation

The `get_data` tool pulls raw economic statistics from the BEA. When you use it with Pydantic AI, every response is automatically parsed and validated against your data models. If the BEA API ever changes its output—adds a field, changes a data type—you'll know instantly. Pydantic AI will raise a `ValidationError` instead of letting corrupted data flow silently into your application. For financial modeling, that's not a feature; it's a requirement.

Model-Agnostic Economic Analysis

These tools give you structured access to official US economic data. You get a list of available datasets with `get_dataset_list` and can then drill down to pull exactly what you need. Since Pydantic AI is model-agnostic, you can use these tools with any LLM—OpenAI, Anthropic, a local model, whatever. The MCP Server handles the connection to the BEA; Pydantic AI handles the data validation. You just focus on the analysis.

Setup guide

Set up BEA (Bureau of Economic Analysis) 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": {
        "bea-bureau-of-economic-analysis-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to BEA (Bureau of Economic Analysis) tools.",
)

result = await agent.run("List recent BEA (Bureau of Economic Analysis) 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 BEA (Bureau of Economic Analysis). 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 BEA (Bureau of Economic Analysis) MCP in Pydantic AI

Make sure you have `pydantic-ai-slim[mcp]` installed. Then instantiate an `MCPToolset` with your Vinkius server URL and add it to your agent's `toolsets` list. That's it.

When your agent calls `get_data` for GDP figures, Pydantic AI will validate the response against a Pydantic model you define. If the data doesn't match the expected structure, like a number coming back as a string, it will throw an error, protecting your application from bad data.

Yes. Your agent would first use `get_parameter_list` to confirm 'Year' is a valid parameter for the dataset. Then, it would call `get_parameter_values` on the 'Year' parameter to get a list of all available years directly from the BEA.

This MCP Server acts as a secure proxy directly to the official BEA public API. It translates your agent's request into a properly formatted API call and returns the response.

Your agent only transmits the specific API parameters needed for the BEA query, such as the requested dataset and table name. This request is processed by the ephemeral Vinkius MCP instance and is not logged or stored. Your Pydantic models and application code are never sent.

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