How to Use the Dopplio MCP in Pydantic AI

Q: How do I register the Dopplio MCP Server inside a Pydantic AI agent?

Install the package with pip install "pydantic-ai-slimmcp". Use the unified MCPToolset to connect to the MCP Server using MCPToolset("YOURVINKIUSURL") and pass it inside the toolsets list when initializing your Agent instance.

Q: How does Pydantic AI validate responses from the Dopplio video generation tool?

The framework inspects the JSON payload returned by generatevideo and parses it against its internal schemas. If the API returns unexpected fields, Pydantic AI raises a validation error instead of passing dirty data to your application.

Build type-safe video outreach pipelines with Pydantic AI, validating every single rendering payload before it hits Dopplio.

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Connect Dopplio MCP to Pydantic AI

Create your Vinkius account to connect Dopplio 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 Dopplio with Pydantic AI

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Type-safe video generation with Pydantic AI

The `generate_video` tool lets your agent kick off video personalization with strict runtime validation of your template variables. Pydantic AI ensures that every dynamic field matches your schema before sending the payload to the rendering engine. If your agent tries to send an invalid email format or missing personalization key, the framework raises a validation error immediately. This stops corrupted payloads from breaking your rendering pipeline and wasting API credits.

Strict schema validation for PDF rendering

The `render_pdf` tool converts raw HTML or target URLs into high-quality PDF files with guaranteed schema compliance. Your agent passes the rendering parameters through a defined Pydantic model, ensuring the output structure is always predictable. If the external API changes or returns unexpected metadata, your agent catches the type mismatch instantly. This prevents downstream tasks from processing incomplete files or corrupted PDFs silently.

Safe video metadata querying

The `get_video_details` tool retrieves the exact status, duration, and download URL of a completed video asset. By passing these results through Pydantic models, you guarantee that your database receives clean, validated URLs. To configure this, connect to the MCP Server using the unified `MCPToolset` constructor and pass it directly to your agent's `toolsets` argument. The toolset handles the underlying SSE or HTTP transport while enforcing strict type-checking on every response.

Setup guide

Set up Dopplio 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": {
        "dopplio-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

result = await agent.run("List recent Dopplio 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 Dopplio. 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 Dopplio MCP in Pydantic AI

Install the package with `pip install "pydantic-ai-slim[mcp]"`. Use the unified MCPToolset to connect to the MCP Server using `MCPToolset("YOUR_VINKIUS_URL")` and pass it inside the `toolsets` list when initializing your `Agent` instance.

The framework inspects the JSON payload returned by `generate_video` and parses it against its internal schemas. If the API returns unexpected fields, Pydantic AI raises a validation error instead of passing dirty data to your application.

Yes, the toolset supports both SSE and Streamable HTTP transports. You can configure your external server connection to use either protocol depending on your network topology and latency requirements.

Yes, you can define a strict Pydantic model for your HTML input and validate it before passing it to `render_pdf`. This ensures your agent only sends well-formed markup to the rendering service.

Your HTML inputs, target URLs, and MP4 renders are processed in secure, ephemeral sandboxes. Vinkius manages the underlying MCP Server infrastructure with strict access controls, ensuring your generated assets are never cached permanently or exposed.

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