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FRED Series — U.S. Economic Time Series MCP Server for Pydantic AI 5 tools — connect in under 2 minutes

Name: FRED Series — U.S. Economic Time Series
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 5 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect FRED Series — U.S. Economic Time Series through the 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 Series — U.S. Economic Time Series "
            "(5 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in FRED Series — U.S. Economic Time Series?"
    )
    print(result.data)

asyncio.run(main())

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About FRED Series — U.S. Economic Time Series MCP Server

Connect your AI agent to the most powerful economic data engine in the world. FRED Series gives you direct access to the Federal Reserve's complete time series database.

Pydantic AI validates every FRED Series — U.S. Economic Time Series tool response against typed schemas, catching data inconsistencies at build time. Connect 5 tools through the 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

Search 816,000+ Series — Find any economic indicator by keyword. GDP, CPI, unemployment rate, federal funds rate, housing starts, and hundreds of thousands more
Retrieve Observations — Get actual date/value pairs with built-in unit transformations (percent change, log, year-over-year) and frequency aggregation (daily → monthly → quarterly → annual)
Series Metadata — Full details: title, units, frequency, seasonal adjustment, observation range, source, and notes
Recent Updates — Monitor which series were just updated — essential for tracking economic releases
Vintage Analysis — Access ALFRED-style historical revisions to understand how data was revised over time

Popular Series IDs

GDP · UNRATE · CPIAUCSL · FEDFUNDS · DGS10 · SP500 · M2SL · MORTGAGE30US · DEXUSEU · T10YIE

The FRED Series — U.S. Economic Time Series MCP Server exposes 5 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 Series — U.S. Economic Time Series to Pydantic AI via MCP

Follow these steps to integrate the FRED Series — U.S. Economic Time Series 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 5 tools from FRED Series — U.S. Economic Time Series with type-safe schemas

Why Use Pydantic AI with the FRED Series — U.S. Economic Time Series MCP Server

Pydantic AI provides unique advantages when paired with FRED Series — U.S. Economic Time Series 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 Series — U.S. Economic Time Series 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 Series — U.S. Economic Time Series connection logic from agent behavior for testable, maintainable code

FRED Series — U.S. Economic Time Series + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the FRED Series — U.S. Economic Time Series MCP Server delivers measurable value.

Type-safe data pipelines: query FRED Series — U.S. Economic Time Series with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple FRED Series — U.S. Economic Time Series tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query FRED Series — U.S. Economic Time Series and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock FRED Series — U.S. Economic Time Series responses and write comprehensive agent tests

FRED Series — U.S. Economic Time Series MCP Tools for Pydantic AI (5)

These 5 tools become available when you connect FRED Series — U.S. Economic Time Series to Pydantic AI via MCP:

get_observations

Supports date filtering, unit transformations (percent change, log, etc.), and frequency aggregation. This is the primary tool for retrieving economic data. Get actual data values for a FRED time series

get_series

Use well-known IDs like GDP, UNRATE, CPIAUCSL, FEDFUNDS, DGS10, SP500, M2SL. Get metadata for a specific FRED series

get_series_updates

Useful for monitoring new data releases. Filter by macro (large/popular series) or regional. Get recently updated FRED series

get_vintage_dates

Essential for ALFRED-style vintage analysis and understanding data revisions. Get historical revision dates for a series

search_series

Returns matching series with title, frequency, units, popularity. Use order_by=popularity to find the most-used series. Examples: "GDP", "unemployment rate", "inflation CPI". Search 816,000+ economic time series by keyword

Example Prompts for FRED Series — U.S. Economic Time Series in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with FRED Series — U.S. Economic Time Series immediately.

"What is the current U.S. unemployment rate?"

"Show me U.S. GDP growth rate over the last 5 years"

"Compare the federal funds rate with 10-year Treasury yield"

Troubleshooting FRED Series — U.S. Economic Time Series MCP Server with Pydantic AI

Common issues when connecting FRED Series — U.S. Economic Time Series to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

FRED Series — U.S. Economic Time Series + Pydantic AI FAQ

Common questions about integrating FRED Series — U.S. Economic Time Series 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 Series — U.S. Economic Time Series MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.