How to Use the Mailify (Sarbacane) MCP in Pydantic AI

Q: How do I initialize the Mailify (Sarbacane) toolset in Pydantic AI?

Install the pydantic-ai-slimmcp package and use the unified MCP HTTP toolset class with your Vinkius HTTP URL. Pass this toolset directly into your agent's toolsets parameter.

Build type-safe email marketing pipelines with Pydantic AI and Mailify (Sarbacane).

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Connect Mailify (Sarbacane) MCP to Pydantic AI

Create your Vinkius account to connect Mailify (Sarbacane) 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 Mailify (Sarbacane) with Pydantic AI

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Validate contact schemas at runtime using Pydantic AI

This MCP Server exposes lists and contact managers like `add_contact_to_book` and `update_book_contact`. When your agent processes a new subscriber, the framework validates the email format and custom fields against strict Python models before hitting the API. Catching validation errors early prevents malformed payloads from reaching your marketing platform. If a field mismatch occurs, the agent catches the error immediately instead of failing silently mid-run.

Type-safe campaign reporting with this MCP Server

The `get_campaign_performance` and `get_campaign_details` tools return raw marketing metrics directly to your Python code. Pydantic AI parses these responses into structured models, ensuring your analytics scripts receive clean data. You can use any LLM with this setup since the validation happens at the framework level. The agent extracts the click rates, open rates, and delivery numbers, guaranteeing your reports are always accurate.

Automate subscriber lifecycle management safely

The `list_address_books` and `list_book_contacts` tools give you programmatic access to your active subscriber databases. Your agent can query lists, identify unengaged users, and call `delete_book_contact` to clean your lists. Because every step is strictly typed, your agent won't accidentally pass a null ID or delete contacts from the wrong list. You get reliable, automated list hygiene with zero guesswork.

Setup guide

Set up Mailify (Sarbacane) 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": {
        "mailify-sarbacane-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about Mailify (Sarbacane) MCP in Pydantic AI

Install the `pydantic-ai-slim[mcp]` package and use the unified MCP HTTP toolset class with your Vinkius HTTP URL. Pass this toolset directly into your agent's `toolsets` parameter.

The Pydantic AI agent will raise a validation error at runtime. This prevents your system from processing corrupt metrics or saving invalid data to your internal databases.

Yes. You can use this server with OpenAI, Anthropic, Gemini, or local models. The tool schemas and runtime validations work identically across all LLM providers.

The tool returns structured contact lists that your agent can iterate through. You can instruct the agent to inspect the response details and make sequential calls to retrieve all records.

Vinkius runs the server in an ephemeral, zero-trust V8 isolate. Your contact records, list details, and API keys are processed entirely in memory and never written to disk, keeping your CRM data secure.

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