How to Use the Dog CEO MCP in AutoGen

Q: How do I register the Dog CEO MCP Server with AutoGen?

Use mcpservertools with StreamableHttpServerParams pointing to your Vinkius endpoint, then pass the resulting tool list to your AutoGen AssistantAgent constructor.

Let AutoGen agents debate breed classifications and fetch dog images using this MCP Server.

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Connect Dog CEO MCP to AutoGen

Create your Vinkius account to connect Dog CEO 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 Dog CEO with AutoGen

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Resolve breed taxonomy via AutoGen debates

The `list_dog_breeds` tool provides the definitive breed list that your AutoGen agents use to settle classification disputes. During a multi-agent conversation, a research agent can call this tool to verify if a breed exists before a writer agent drafts content. This consensus-driven workflow stops incorrect breed names from entering your final output. The agents coordinate automatically, passing the raw breed list between themselves to validate user inputs.

Verify breed images using MCP Server consensus

The `get_dog_by_breed` tool fetches breed-specific image URLs that your AutoGen agents cross-reference for accuracy. One agent retrieves the image, while a second agent inspects the metadata to ensure it matches the requested breed. This division of labor prevents your conversational systems from outputting broken or mismatched links. The McpToolAdapter handles the schema conversion, letting your agents focus on negotiating the correct output.

Inject random images into AutoGen group chats

The `get_random_dog_image` tool injects random dog images into your AutoGen agent conversations when the group decides a visual break is needed. The coordinator agent decides when to trigger the tool based on chat dynamics. You configure this by passing the tool list generated by StreamableHttpServerParams to your AssistantAgent. This gives the entire agent cluster immediate access to the dog image database.

Setup guide

Set up Dog CEO 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 Dog CEO 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="Dog CEO_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Dog CEO 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="Dog CEO_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Dog CEO 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 Dog CEO. 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 Dog CEO MCP in AutoGen

Use mcp_server_tools with StreamableHttpServerParams pointing to your Vinkius endpoint, then pass the resulting tool list to your AutoGen AssistantAgent constructor.

Yes, the MCP server handles concurrent requests. Your agents can debate breed classifications and pull images via get_dog_by_breed simultaneously during a group chat.

Yes, the McpToolAdapter in AutoGen translates the schemas of list_dog_breeds and other tools into the format your AssistantAgent expects without manual mapping.

Yes, AutoGen supports both transport layers. You configure the connection parameters depending on whether you are running the agent locally or in a distributed network.

The MCP server only sees the specific breed string sent to the API to fetch images. Your multi-agent conversation logs, prompt histories, and agent system instructions are completely isolated and never exposed.

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