How to Use the Mod.io MCP in AutoGen

Q: How do I coordinate Mod.io tools between AutoGen agents?

List your tools in the AssistantAgent configuration. The agents automatically decide which member of the team should invoke the Mod.io function.

Q: How do I limit Mod.io access for specific AutoGen agents?

Assign tools to specific agents. Only the agent with the subscribemod capability can perform that action, keeping your workflow secure.

Debate your mod strategy with AutoGen. Let agents negotiate mod.io actions through multi-agent deliberation.

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Connect Mod.io MCP to AutoGen

Create your Vinkius account to connect Mod.io 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 Mod.io with AutoGen

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Consensus-Driven Subscriptions

Assign a curator agent to call `get_mods` and a security agent to check for risks. They debate the value of a mod before calling `subscribe_mod`. This prevents bad actors or low-quality content from entering your library. The agents negotiate until they reach a decision that satisfies your criteria.

Negotiated Mod Ratings

Let your agents analyze `get_game_stats` to determine if a mod deserves a high rating. The agents discuss the data and call `rate_mod` only when they agree. You see the full transcript of their deliberation. It shows exactly why a particular rating was chosen based on the API feedback.

Collaborative Collection Management

Use multiple agents to organize `get_collections`. One agent fetches the list, while another filters it based on player feedback, ensuring your collections remain relevant. They work as a team to maintain your mod library. Each agent brings a different perspective to the management process.

Setup guide

Set up Mod.io 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 Mod.io 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="Mod.io_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Mod.io 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="Mod.io_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Mod.io 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 Mod.io. 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 Mod.io MCP in AutoGen

List your tools in the `AssistantAgent` configuration. The agents automatically decide which member of the team should invoke the Mod.io function.

Yes. Agents share the context window, allowing them to pass the results of `get_me` to subsequent tools in the conversation flow.

You manage the flow by setting agent conversation limits. If an error occurs, the agents can discuss a retry strategy or log the incident.

Assign tools to specific agents. Only the agent with the `subscribe_mod` capability can perform that action, keeping your workflow secure.

Only the agents currently in the active conversation have access to the tool outputs. Your credentials are never stored in the agent's long-term memory.

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