How to Use the Convertio MCP in Pydantic AI

Convert files with type-safe reliability using Pydantic AI and this MCP Server.

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Connect Convertio MCP to Pydantic AI

Create your Vinkius account to connect Convertio 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 Convertio with Pydantic AI

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Pydantic AI server connectivity

Use the MCPToolset to register the server and start processing files. Every request is validated against your schema at runtime. Call `convert_file` to start a task. If the API returns a malformed response, your agent will catch it immediately.

Type-safe file conversion tools

Run `quick_convert_to_jpg` to get image outputs. Because you are using Pydantic AI, you know exactly what the output structure looks like. Use `list_common_formats` to fetch the list of supported types. The framework validates this list before your code even sees it.

Manage job states with validation

Track your progress with `get_conversion_status`. The response is checked against your model to ensure the status fields are correct. Clean up after yourself with `delete_conversion_job`. It ensures your remote environment stays clean and predictable.

Setup guide

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

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

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

Use the MCPToolset class with your server URL. Pass it into your agent's toolsets parameter to enable all eight conversion operations.

You get runtime validation on every tool response. If the conversion service returns an unexpected field or format, the agent fails before it can process bad data.

It does. You can use SSE or Streamable HTTP transports to connect to the server. The toolset handles the connection logic for you.

The tool will return a structured error response that the agent handles gracefully. Since you have strict models, you can define exactly how to retry or alert.

The server only processes files via URL. All file metadata and binary content are purged from the conversion service when you invoke the deletion tool, ensuring no residual data remains.

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