How to Use the Tuputech Moderation MCP in AutoGen

Q: Can Tuputech Moderation handle complex streams for AutoGen?

Yes. You can incorporate asynchronous checks like scanaudiostream or scanvideostream into the discussion, forcing multiple agents to analyze and debate the media's content.

Q: Does Tuputech Moderation support user feedback with AutoGen?

The system supports this. You can use the submitfeedback tool as part of a dedicated 'Review Agent' that feeds manual data back to improve the model.

Run multi-agent moderation debates with AutoGen. Achieve consensus on content safety using the MCP Server's tools.

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Connect Tuputech Moderation MCP to AutoGen

Create your Vinkius account to connect Tuputech Moderation 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 Tuputech Moderation with AutoGen

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Perplexity

Debating content safety across multiple agents

Assign different roles to your agents: one can run `scan_image_porn` (the Safety Agent), and another runs `scan_text_abuse` (the Policy Agent). These two agents then debate the risk level based on their individual findings. The final answer isn't just a score; it's a negotiated consensus. AutoGen forces deliberation, giving you confidence that competing perspectives were weighed.

Consensus checking with MCP Server for AutoGen

You can set up agents to check different aspects of media concurrently. One agent handles `scan_video_stream` (the Performance Agent), while another runs `scan_image_synthetic` (the Authenticity Agent). They must agree on the final risk assessment. This is perfect for high-stakes decisions where a single tool call isn't enough—you need agreement.

Automated spam and ad detection debate

Need to verify if submitted content is clean? Have one agent run `scan_text_spam` while another runs `scan_image_ad`. They compare results: 'The text is fine, but the image has embedded ads.' This structured debate prevents false positives by requiring multiple tools and agents to confirm a status.

Setup guide

Set up Tuputech Moderation 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 Tuputech Moderation 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="Tuputech Moderation_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Tuputech Moderation 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="Tuputech Moderation_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Tuputech Moderation data")
    print(result.messages[-1].content)

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Common questions about Tuputech Moderation MCP in AutoGen

You give different moderation tools to different agents. They then talk through the results, challenging each other's conclusions until they reach a final, consensus-driven verdict.

Assign specialized roles: one agent focuses on text policy (`scan_text_politics`), and another focuses on media integrity (`scan_image_terrorism`). They debate the content's suitability.

Yes. You can incorporate asynchronous checks like `scan_audio_stream` or `scan_video_stream` into the discussion, forcing multiple agents to analyze and debate the media's content.

The system supports this. You can use the `submit_feedback` tool as part of a dedicated 'Review Agent' that feeds manual data back to improve the model.

This MCP Server handles text, images, audio streams, and video streams. These diverse inputs allow your agents to debate risk across many media formats.

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