How to Use the Ape Wisdom MCP in AutoGen

Let your AutoGen agents debate market trends using data from the Ape Wisdom MCP Server.

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Connect Ape Wisdom MCP to AutoGen

Create your Vinkius account to connect Ape Wisdom to AutoGen 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 Ape Wisdom with AutoGen

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Debate market sentiment with AutoGen

Assign one agent to run `get_sentiment_leaders` while another critiques the findings. The agents negotiate based on the actual asset data. Your system reaches a consensus by challenging the results of `list_wallstreetbets`. One agent acts as the analyst, the other as the skeptic.

Automate agent research with Ape Wisdom

Use `list_trending_subreddit` to gather raw data for your research agent. The agent then shares these findings with the group for discussion. Multiple agents parse the output of `list_trending_stocks` simultaneously. They converge on a decision by comparing the data against their individual constraints.

Configure AutoGen for market deliberation

Pass the tool list to your `AssistantAgent` to start the conversation. The MCP adapter handles the schema so your agents understand the tools immediately. Your security agent flags risky assets found by `list_trending_crypto`. Meanwhile, the performance agent pushes to get the latest trends from `get_market_snapshot` as fast as possible.

Setup guide

Set up Ape Wisdom 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 Ape Wisdom 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="Ape Wisdom_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Ape Wisdom 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="Ape Wisdom_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Ape Wisdom 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 Ape Wisdom. 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 Ape Wisdom MCP in AutoGen

Use the autogen-ext MCP package to connect. Pass the server tools directly into your assistant agent constructor.

Yes, you can share the MCP tools across your agent team. They will coordinate and debate the data they pull from the server.

It provides the data that fuels the debate. Your agents use the tools to support their arguments during the conversation.

We use an ephemeral V8 sandbox to process your requests. Your ticker lists and sentiment data are discarded once your agent session ends.

We maintain a zero-trust architecture. Your specific search parameters are private to your endpoint and never leak between agent sessions.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript

Mastra AI sdk-typescript

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