How to Use the ECB Monetary — Money Supply, Yield Curves & Banknotes MCP in AutoGen

Q: How do I add the ECB Monetary — Money Supply, Yield Curves & Banknotes tools to AutoGen?

Install autogen-extmcp. Initialize StreamableHttpServerParams with your endpoint, fetch the tools, and pass them to your AssistantAgent. The adapter handles schema conversion automatically.

Give your AutoGen agents the live ECB yield curve and money supply data they need to debate macro strategy.

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Connect ECB Monetary — Money Supply, Yield Curves & Banknotes MCP to AutoGen

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Setup ECB Monetary — Money Supply, Yield Curves & Banknotes with AutoGen

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Perplexity

Debate Monetary Policy with Live M3 Data

Complex macro decisions require opposing viewpoints. You build one AutoGen agent to argue for tightening based on inflation, and another to argue for easing. They need hard numbers. They use `get_monetary_aggregate` to pull the latest M1, M2, and M3 supply figures. The hawkish agent points to M3 expansion as proof of systemic risk. The dovish agent counters using the same dataset. They debate the meaning of the overnight deposit shifts. You watch them negotiate a consensus forecast based on real central bank data.

AutoGen Debates with the MCP Server

When the yield curve inverts, your risk management agent needs to sound the alarm. It calls `get_yield_curve_snapshot` to pull the exact AAA-rated government bond rates across all maturities. A separate portfolio agent reviews the snapshot. It challenges the risk agent's conclusion, arguing that the 3-month to 10-year spread isn't wide enough to guarantee a recession. The framework handles the back-and-forth automatically until they reach a shared policy recommendation.

Cross-Reference Cash Hoarding and Debt

Physical cash hoarding signals market panic. Your liquidity agent monitors this by pulling monthly €5 to €500 circulation stats via `get_banknotes`. A fixed-income agent simultaneously checks 30-year sovereign debt trends using `get_yield_curve`. They cross-reference physical cash demand against long-term bond yields. The result is a deeply researched, multi-perspective analysis that a single LLM prompt could never generate.

Setup guide

Set up ECB Monetary — Money Supply, Yield Curves & Banknotes 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 ECB Monetary — Money Supply, Yield Curves & Banknotes 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="ECB Monetary — Money Supply, Yield Curves & Banknotes_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent ECB Monetary — Money Supply, Yield Curves & Banknotes 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="ECB Monetary — Money Supply, Yield Curves & Banknotes_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent ECB Monetary — Money Supply, Yield Curves & Banknotes 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 European Central Bank. 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 ECB Monetary — Money Supply, Yield Curves & Banknotes MCP in AutoGen

Install `autogen-ext[mcp]`. Initialize `StreamableHttpServerParams` with your endpoint, fetch the tools, and pass them to your `AssistantAgent`. The adapter handles schema conversion automatically.

Yes. The framework shares the tool definitions across your agent roster. A risk agent and a forecasting agent can both request yield curve data during their conversation.

Macroeconomics is subjective. One agent pulling M3 data might misinterpret it. Having multiple agents debate the exact same eurozone statistics forces a more accurate, balanced conclusion.

The LLM decides based on the user prompt. If you ask about short-term liquidity, the agent knows to request 3-month or 6-month rates from the tool.

No. The server only receives the specific tool arguments required to fetch M3 aggregates, banknote totals, or bond yields. Your multi-agent debates remain entirely private, protected by Vinkius's ephemeral architecture.

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