How to Use the FRED Full Access — U.S. Economic Intelligence MCP in OpenAI Agents SDK

Q: How do I integrate FRED Full Access — U.S. Economic Intelligence with my OpenAI Agents SDK project?

Install the library and define an MCPServerStreamableHttp instance. Pass this object into your agent's constructor to enable automatic tool discovery.

Q: Does FRED Full Access — U.S. Economic Intelligence work with OpenAI Agents SDK tool caching?

Yes, use cacheToolsList=True to improve performance. This prevents the agent from re-querying the server's tool schema on every single interaction.

Build reliable economic agents with FRED Full Access — U.S. Economic Intelligence and the OpenAI Agents SDK.

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Connect FRED Full Access — U.S. Economic Intelligence MCP to OpenAI Agents SDK

Create your Vinkius account to connect FRED Full Access — U.S. Economic Intelligence to OpenAI Agents SDK 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 FRED Full Access — U.S. Economic Intelligence with OpenAI Agents SDK

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Automate data retrieval in OpenAI Agents SDK

Your agent pulls real-time macroeconomic indicators without manual scraping. It triggers `get_observations` to grab specific data points and feeds them directly into your agent's decision loop. You save hours of manual entry. The agent handles the back-and-forth, ensuring your financial models use current federal data every time it runs.

Perform vintage analysis for model training

Use `get_vintage_dates` to avoid look-ahead bias in your training sets. You see exactly how the data looked on a specific date, preventing your agent from using future revisions during backtesting. This keeps your agent's logic grounded in historical reality. It's the difference between a model that works in a vacuum and one that survives actual market conditions.

Discover series with OpenAI Agents SDK

Search 816,000+ series using `search_series` to find the exact economic metric you need. The agent parses titles and popularity scores to select the most relevant data source for your inquiry. Stop guessing which series ID matches your requirement. Your agent finds the right metadata and validates it before pulling the full observation set.

Setup guide

Set up FRED Full Access — U.S. Economic Intelligence MCP in OpenAI Agents SDK

Prerequisites

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

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all FRED Full Access — U.S. Economic Intelligence tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives FRED Full Access — U.S. Economic Intelligence tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate FRED Full Access — U.S. Economic Intelligence tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="FRED Full Access — U.S. Economic Intelligence Agent",
            instructions="You have access to FRED Full Access — U.S. Economic Intelligence tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about FRED Full Access — U.S. Economic Intelligence MCP in OpenAI Agents SDK

Install the library and define an `MCPServerStreamableHttp` instance. Pass this object into your agent's constructor to enable automatic tool discovery.

Yes, use `cacheToolsList=True` to improve performance. This prevents the agent from re-querying the server's tool schema on every single interaction.

Absolutely. The server provides the raw data, and the SDK's built-in guardrails manage the execution flow. It's built for production workloads.

The server exposes 816,000+ series. Watch your request frequency, as the underlying Federal Reserve API enforces its own rate limits.

Your agent only touches public economic time series. No personal or proprietary information is ever transmitted or stored by this MCP server during your analysis.

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