How to Use the TopOn / Mobvista MCP in Pydantic AI

Q: Can I use Pydantic AI for Mintegral reporting from TopOn / Mobvista?

Yes. When you call getmintegralreporting, the resulting data set is forced into a predictable Python type structure. This makes complex analysis much safer and more reliable.

Q: What kind of waterfall data can Pydantic AI process from TopOn / Mobvista?

You can use gettoponwaterfall, and the output will be typed. This guarantees that every placement, eCPM value, or revenue metric is correctly formatted for your subsequent code execution.

Q: Does Pydantic AI support listing placements from TopOn / Mobvista?

Yes. Calling listtoponplacements provides a list that is validated at runtime. This means you get clean, consistent data every time the ad units change.

Ensure perfect ad monetization data integrity using Pydantic AI and TopOn / Mobvista MCP Server.

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Connect TopOn / Mobvista MCP to Pydantic AI

Create your Vinkius account to connect TopOn / Mobvista 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 TopOn / Mobvista with Pydantic AI

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Get Mintegral App Stats with Validation

When calling `get_mintegral_app_stats`, every single field returned is validated against a Pydantic schema. You never get unexpected or corrupted ad data, guaranteeing accuracy. This level of type safety means your agent can trust the inputs it's using for critical business decisions.

Process TopOn Monetization Summaries

Running `get_monetization_summary` produces data that is strictly validated. If the API sends back a field that doesn't match your model, the agent fails immediately with an error—no silent issues. It forces correctness. You always know exactly what structure of ad performance summary you are dealing with.

List All Ad Placements and Offers

Use `list_topon_placements` or `list_mintegral_offers`, and the resulting list is guaranteed to conform to a predictable structure. This prevents your agent from breaking when ad platforms update their underlying API format. It keeps your data pipeline rock solid, focusing on correctness over speed.

Setup guide

Set up TopOn / Mobvista 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": {
        "topon-mobvista-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

result = await agent.run("List recent TopOn / Mobvista transactions")
print(result.output)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by TopOn / Mobvista. 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 TopOn / Mobvista MCP in Pydantic AI

The MCP Server outputs are validated by Pydantic models. This means when your agent uses tools like `get_topon_reporting`, the data structure is guaranteed to be correct, eliminating bad inputs.

Yes. When you call `get_mintegral_reporting`, the resulting data set is forced into a predictable Python type structure. This makes complex analysis much safer and more reliable.

You can use `get_topon_waterfall`, and the output will be typed. This guarantees that every placement, eCPM value, or revenue metric is correctly formatted for your subsequent code execution.

The server touches monetization and ad placement stats. Because the output is strictly typed, only necessary metrics are passed to your agent, improving both security and reliability.

Yes. Calling `list_topon_placements` provides a list that is validated at runtime. This means you get clean, consistent data every time the ad units change.

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