How to Use the FRED GeoFRED — Regional Economic Data MCP in AutoGen

Q: How do AutoGen agents share data from FRED GeoFRED — Regional Economic Data?

Agents share the output of getregionaldata through the group chat context. One agent fetches the data, and others analyze or challenge the findings in subsequent conversation turns.

Q: Can I use FRED GeoFRED — Regional Economic Data with AutoGen's AssistantAgent?

Yes. Register the MCP server tools and pass them to the AssistantAgent constructor. The agent will then call getseriesgroup and other tools as needed.

Set up AutoGen agents to debate and analyze regional economic trends using live, authenticated Fed data.

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Connect FRED GeoFRED — Regional Economic Data MCP to AutoGen

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Setup FRED GeoFRED — Regional Economic Data with AutoGen

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Resolve economic metadata using this MCP Server

`get_series_group` is the tool your coordinator agent uses to find regional series group IDs and geographic metadata. It translates generic queries about local trends into specific, actionable FRED series groups. In an AutoGen group chat, this metadata is shared with other agents to align their analysis. For example, a data-retrieval agent passes the discovered region types to an analyst agent to ensure they are debating the same geographic boundaries.

Feed regional metrics into multi-agent debates

`get_regional_data` fetches the localized economic statistics that fuel agent discussions. Whether you need county-level unemployment or MSA-level income, this tool provides the raw numbers directly to the conversation. This MCP Server allows your agents to argue with facts. A policy agent challenges a budget agent's assumptions by pulling real-time county GDP data, forcing a consensus based on official Federal Reserve numbers rather than assumptions.

Query geographic shapes for spatial verification

`get_geo_shapes` retrieves spatial boundaries for counties, states, and metro areas. This tool lets your agents verify geographic boundaries before finalizing regional economic reports. When an agent generates a report, a validation agent uses the coordinates returned by this tool to check if the economic data matches the physical boundaries. This ensures that your automated reporting is geographically accurate.

Setup guide

Set up FRED GeoFRED — Regional Economic Data MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes FRED GeoFRED — Regional Economic Data tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="FRED GeoFRED — Regional Economic Data_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent FRED GeoFRED — Regional Economic Data data")
print(result.messages[-1].content)

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Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="FRED GeoFRED — Regional Economic Data_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent FRED GeoFRED — Regional Economic Data data")
    print(result.messages[-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by FRED. 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 FRED GeoFRED — Regional Economic Data MCP in AutoGen

Agents share the output of `get_regional_data` through the group chat context. One agent fetches the data, and others analyze or challenge the findings in subsequent conversation turns.

Yes. Register the MCP server tools and pass them to the `AssistantAgent` constructor. The agent will then call `get_series_group` and other tools as needed.

The MCP tool adapter in the AutoGen extension handles all schema conversion automatically. Your agents can call `get_geo_shapes` using standard JSON payloads without manual translation.

The FRED API limit is 120 requests per minute. Configure your AutoGen orchestrator to pace agent tool calls or implement a local caching layer to avoid hitting this ceiling.

The server only processes public economic indicators and geographic shapes. Your Vinkius connection is isolated in a secure sandbox, ensuring that your agent conversations and API keys remain completely private.

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