How to Use the Findymail MCP in Pydantic AI

Q: How do I set up the Findymail MCP Server in Pydantic AI?

You use the MCPToolset class and pass it your Vinkius HTTP URL. Then, add it to your agent's toolsets list to enable the available functions.

Get type-safe prospecting results in Pydantic AI using the Findymail MCP Server.

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Connect Findymail MCP to Pydantic AI

Create your Vinkius account to connect Findymail 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 Findymail with Pydantic AI

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Type-Safe Prospecting for Pydantic AI

Every response from `find_email` is validated against your Pydantic models at runtime. If the output doesn't match your expected format, the agent throws an error immediately. This prevents silent data corruption. You can trust that the contact details passed to your next step are perfectly formatted.

Strict Verification for Pydantic AI Agents

Your agent uses `verify_email` to check prospect validity with full schema enforcement. It ensures the data returned is exactly what your logic requires. This strict approach catches edge cases early. You avoid runtime crashes caused by unexpected API responses.

Handling Search Results in Pydantic AI

The agent calls `get_lead_search_data` and maps the output directly into your defined models. You get clean, typed data ready for your business logic. It removes the need for manual parsing or validation. Your code stays concise and reliable.

Setup guide

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

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

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

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Common questions about Findymail MCP in Pydantic AI

You use the `MCPToolset` class and pass it your Vinkius HTTP URL. Then, add it to your agent's `toolsets` list to enable the available functions.

Yes, every tool output is validated against your schema. If the server sends unexpected data, the framework alerts you immediately so you can handle the error.

You can. The framework is model-agnostic, so it works with local models or cloud-based ones while communicating with the server.

The framework raises a validation error if the response fails to match your model. This forces your code to handle the failure explicitly rather than continuing with bad data.

We enforce strict type-checking and isolate all tool execution in a secure sandbox. Your lead names and email addresses never leak between different agent instances.

Use it with your favorite AI tools

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