How to Use the Tuputech Moderation MCP in Pydantic AI

Q: Can I check for AI-generated images using Tuputech Moderation with the Pydantic AI?

Yes, you can use scanimagesynthetic. The resulting data structure is validated by Pydantic, so you'll get a reliable flag indicating if the image source is suspicious.

Q: Does Tuputech Moderation handle video scanning with the Pydantic AI?

It does. You can initiate scanvideostream. The resulting metadata stream will be validated against your schema, giving you structured data about the scan status.

Q: If I need to improve moderation rules, how does Tuputech Moderation and the Pydantic AI help?

You submit manual feedback via submitfeedback. This process feeds back into the system, which then improves the data quality of the results you receive.

Ensure perfect data output from moderation checks using Pydantic AI.

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Connect Tuputech Moderation MCP to Pydantic AI

Create your Vinkius account to connect Tuputech Moderation to Pydantic AI 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 Pydantic AI

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Perplexity

Validate text for political compliance

The agent uses `scan_text_politics` to check incoming text. Because the response is validated by Pydantic, you're guaranteed a predictable structure (e.g., a boolean and a reason code). This stops silent failures; if the API output changes, your agent fails loudly.

Scan images for pornographic content

You can run `scan_image_porn` on media. The result is validated against a Pydantic schema, ensuring you get exactly the data fields you expect—no corrupted or missing values. It's about correctness first; knowing that your moderation output structure won’t break downstream code.

Detect ads in images and text

The agent handles two types of checks: `scan_image_ad` for visuals, and `scan_text_spam` for text. Both results flow into Pydantic models. This means your final data object always contains consistent fields detailing the presence or absence of spam/ads.

Setup guide

Set up Tuputech Moderation MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "tuputech-moderation-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Tuputech Moderation tools.",
)

result = await agent.run("List recent Tuputech Moderation transactions")
print(result.output)

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Common questions about Tuputech Moderation MCP in Pydantic AI

The agent treats every moderation response—whether it's from `scan_audio_stream` or any other tool—as data that must conform to a predefined Pydantic model. This guarantees predictable outputs.

Yes, you can use `scan_image_synthetic`. The resulting data structure is validated by Pydantic, so you'll get a reliable flag indicating if the image source is suspicious.

It does. You can initiate `scan_video_stream`. The resulting metadata stream will be validated against your schema, giving you structured data about the scan status.

You submit manual feedback via `submit_feedback`. This process feeds back into the system, which then improves the data quality of the results you receive.

This server touches text, image, audio, and video data types. The Pydantic validation ensures that even when handling diverse media inputs, your agent processes the output reliably.

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