How to Use the Zerion (DeFi Portfolio) MCP in AutoGen

Q: Is Zerion (DeFi Portfolio) suitable for multi-entity analysis in AutoGen?

Totally. The getwalletsetpositions tool allows you to feed multiple accounts into a single debate, letting the agents compare and contrast holdings across various entities.

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Connect Zerion (DeFi Portfolio) MCP to AutoGen

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Setup Zerion (DeFi Portfolio) with AutoGen

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Debating Investment Strategies with MCP Server

A multi-agent system needs deliberation. You can set up a debate where one agent uses `get_swap_quotes` to suggest the best cross-chain bridge, while a second agent checks current gas estimates via `list_gas_prices`. They negotiate whether the potential gain outweighs the network cost. This is consensus-driven decision making in action. The agents argue over the optimal path for funds, leading to a final, validated recommendation based on real-time data inputs from the MCP Server.

Validating Portfolio Risks with AutoGen

You can deploy a security agent that reviews all assets. It uses `get_wallet_nft_positions` to check individual NFT holdings against known risk criteria, while a performance agent simultaneously runs `get_wallet_portfolio` to track total exposure. The agents challenge each other's assumptions. The security agent might flag a high-risk token, and the performance agent counterpoints that the potential upside is worth it—the user gets the deliberation.

Aggregating Complex Data Sets with AutoGen

Managing multiple DeFi accounts requires aggregation. Use `get_wallet_set_transactions` to gather history across several wallets. An agent can then take that massive dataset and compare it against the overall asset distribution from `get_wallet_set_portfolio`. The agents debate which addresses contributed most to the total value, leading to a much deeper analysis than any single tool call could provide.

Setup guide

Set up Zerion (DeFi Portfolio) 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 Zerion (DeFi Portfolio) 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="Zerion (DeFi Portfolio)_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Zerion (DeFi Portfolio) data")
print(result.messages[-1].content)

Get your connection token →

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="Zerion (DeFi Portfolio)_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Zerion (DeFi Portfolio) data")
    print(result.messages[-1].content)

Get your connection token →

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Common questions about Zerion (DeFi Portfolio) MCP in AutoGen

AutoGen treats the MCP Server as an external source of facts. Agents can be assigned roles, like 'Analyst' or 'Risk Checker,' and tasked with using specific tools to gather data for their debate.

You can run a simulation where agents negotiate the optimal time to sell assets. One agent checks PnL, another checks gas prices, and they converge on the best day/time.

Totally. The `get_wallet_set_positions` tool allows you to feed multiple accounts into a single debate, letting the agents compare and contrast holdings across various entities.

It provides comprehensive financial states: token metadata, NFT details, transaction streams, and real-time gas estimates. Everything needed to fuel a debate.

The server touches wallet positions and transaction history. The agents must be programmed only to use the subset of addresses or time ranges that you explicitly permit for analysis.

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