GeoFRED is the geographic extension of FRED. While FRED provides national time series, GeoFRED breaks that data down by state, county, metropolitan area, and Federal Reserve district — enabling regional economic comparisons and choropleth mapping.

FRED GeoFRED — Regional Economic Data MCP Server for Pydantic AI 3 tools — connect in under 2 minutes

Name: FRED GeoFRED — Regional Economic Data
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 3 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect FRED GeoFRED — Regional Economic Data through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

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Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to FRED GeoFRED — Regional Economic Data "
            "(3 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in FRED GeoFRED — Regional Economic Data?"
    )
    print(result.data)

asyncio.run(main())

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About FRED GeoFRED — Regional Economic Data MCP Server

Compare economic performance across U.S. regions. GeoFRED turns national time series into cross-sectional geographic data.

Pydantic AI validates every FRED GeoFRED — Regional Economic Data tool response against typed schemas, catching data inconsistencies at build time. Connect 3 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Regional Snapshots — Unemployment, income, poverty, housing prices per state, county, or MSA
Series Groups — Discover which geographic breakdowns exist for any FRED series
Shape Data — Get GeoJSON-compatible boundaries for mapping

Region Types

state · county · msa · bea (Bureau of Economic Analysis) · frb (Federal Reserve District) · censusregion

The FRED GeoFRED — Regional Economic Data MCP Server exposes 3 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect FRED GeoFRED — Regional Economic Data to Pydantic AI via MCP

Follow these steps to integrate the FRED GeoFRED — Regional Economic Data MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 3 tools from FRED GeoFRED — Regional Economic Data with type-safe schemas

Why Use Pydantic AI with the FRED GeoFRED — Regional Economic Data MCP Server

Pydantic AI provides unique advantages when paired with FRED GeoFRED — Regional Economic Data through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your FRED GeoFRED — Regional Economic Data integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your FRED GeoFRED — Regional Economic Data connection logic from agent behavior for testable, maintainable code

FRED GeoFRED — Regional Economic Data + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the FRED GeoFRED — Regional Economic Data MCP Server delivers measurable value.

Type-safe data pipelines: query FRED GeoFRED — Regional Economic Data with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple FRED GeoFRED — Regional Economic Data tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query FRED GeoFRED — Regional Economic Data and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock FRED GeoFRED — Regional Economic Data responses and write comprehensive agent tests

FRED GeoFRED — Regional Economic Data MCP Tools for Pydantic AI (3)

These 3 tools become available when you connect FRED GeoFRED — Regional Economic Data to Pydantic AI via MCP:

get_geo_shapes

Shape values: bea, msa, frb, necta, state, country, county, censusregion. Get geographic shape files for mapping

get_regional_data

Use get_series_group first to find the series_group ID for a FRED series. Region types: state, county, msa, bea, frb, necta, country, censusregion. Get cross-sectional regional economic data

get_series_group

Enter a FRED series ID (e.g., UNRATE for unemployment) to discover the series_group ID, available region types, units, and seasonality. Get series group info for GeoFRED mapping

Example Prompts for FRED GeoFRED — Regional Economic Data in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with FRED GeoFRED — Regional Economic Data immediately.

"What is the unemployment rate by state?"

"Compare median household income across metro areas"

"Get the geographic boundaries for U.S. states"

Troubleshooting FRED GeoFRED — Regional Economic Data MCP Server with Pydantic AI

Common issues when connecting FRED GeoFRED — Regional Economic Data to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

FRED GeoFRED — Regional Economic Data + Pydantic AI FAQ

Common questions about integrating FRED GeoFRED — Regional Economic Data MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your FRED GeoFRED — Regional Economic Data MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.