How to Use the ShowAPI / 易源数据 MCP in AutoGen

Run debates and consensus checks with AutoGen's multi-agent system.

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Connect ShowAPI / 易源数据 MCP to AutoGen

Create your Vinkius account to connect ShowAPI / 易源数据 to AutoGen — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup ShowAPI / 易源数据 with AutoGen

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Debating Travel Plans using MCP Server

Set up three agents: one for weather, one for currency exchange, and one for local culture. Agent A calls `get_weather` first, then Agent B uses that data to check the best time by calling `get_currency_rates`. Finally, Agent C recommends a suitable phrase using `get_idiom_info`. AutoGen forces these agents to debate the *best* travel plan, achieving consensus on location and timing.

Financial Risk Assessment with AutoGen

Build an advisory system where agents challenge each other's advice. One agent pulls `get_stock_info` data while another monitors global risk using `get_ip_lookup`. They then debate the implications, requiring a third agent to synthesize a final recommendation. This moves beyond simple tool calling; it models actual professional deliberation.

Content Creation Consensus with AutoGen

Need compelling content? Give one agent `get_inspirational_quotes` and another the ability to generate jokes using `get_jokes`. The third 'editor' agent then debates which piece is strongest for a given context, checking definitions via `get_english_dictionary` for tone. AutoGen ensures the final output isn't just random data; it’s agreed-upon content.

Setup guide

Set up ShowAPI / 易源数据 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 ShowAPI / 易源数据 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="ShowAPI / 易源数据_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent ShowAPI / 易源数据 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="ShowAPI / 易源数据_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent ShowAPI / 易源数据 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 ShowAPI / 易源数据. 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 ShowAPI / 易源数据 MCP in AutoGen

You pass the tool definitions from ShowAPI / 易源数据 to the AssistantAgent. The agents then autonomously decide which tools are needed and when they should be called during their conversation.

Yes. It’s designed for complexity. If the answer requires three different pieces of information—like weather, history, and currency—the agents will debate until they gather all three.

Any tool that provides distinct perspectives works well. For instance, comparing `get_stock_info` with a global event report from `get_history_today` creates immediate points of debate.

Yes. The full dialogue is preserved, showing every agent's reasoning, including which MCP Server tools they decided to call and why.

The server touches API data like IP lookup information. When running a debate, you control the scope of the tools available to minimize exposure.

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