How to Use the Maileon MCP in Pydantic AI

Q: How do I initialize the Maileon MCP Server toolset in Pydantic AI?

Install pydantic-ai-slimmcp and instantiate MCPToolset with your Vinkius HTTP endpoint. Pass this toolset instance inside the toolsets argument when defining your Agent.

Q: How does Pydantic AI handle Maileon unsubscription events?

Your agent calls listunsubscriptionevents to retrieve recent opt-outs, which are automatically parsed into typed models. You can then loop through these validated records to update your local databases safely.

Q: Can I remove contacts programmatically using this server?

Yes, you can call deleteaccountcontact with a specific contact ID or email address. The server processes the deletion and returns a confirmation status to your agent.

Build type-safe email marketing workflows using Pydantic AI to validate every Maileon API response at runtime.

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Connect Maileon MCP to Pydantic AI

Create your Vinkius account to connect Maileon 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 Maileon with Pydantic AI

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Validate contacts with Pydantic AI

The `get_contact_by_email` tool retrieves subscriber profiles and validates their structure against strict Pydantic schemas before your agent processes them. This prevents malformed data or missing attributes from crashing your downstream pipelines. When adding new users, `create_new_contact` ensures that only properly formatted email addresses and fields are sent to your database. If the API response deviates from the expected schema, the framework raises an immediate validation error.

Secure campaign execution with this MCP Server

The `dispatch_email_mailing` tool fires off ready campaigns while your Pydantic AI agent monitors the execution state. The framework validates the dispatch response, guaranteeing your code knows exactly when the mailings are successfully sent. To verify which campaigns are ready, `list_email_mailings` pulls current drafts and parses them into typed Python models. Your agent uses these models to safely determine which campaign ID to pass to the dispatch tool.

Parse campaign analytics with strict types

The `get_mailing_statistics` tool delivers raw performance data that is instantly parsed into structured Python objects. This ensures your reporting scripts never fail due to unexpected null values or modified API payloads. For deeper audits, `list_unsubscription_events` tracks opt-out records while `get_mailing_details` inspects structural settings. Your agent relies on these strongly typed datasets to safely update your local databases.

Setup guide

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

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

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

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Common questions about Maileon MCP in Pydantic AI

Install `pydantic-ai-slim[mcp]` and instantiate `MCPToolset` with your Vinkius HTTP endpoint. Pass this toolset instance inside the `toolsets` argument when defining your Agent.

Yes, the framework validates all inputs against the MCP tool schemas before transmitting the request. If your agent attempts to call `create_new_contact` with missing required fields, it fails locally before hitting the API.

Your agent calls `list_unsubscription_events` to retrieve recent opt-outs, which are automatically parsed into typed models. You can then loop through these validated records to update your local databases safely.

Yes, you can call `delete_account_contact` with a specific contact ID or email address. The server processes the deletion and returns a confirmation status to your agent.

Your contact profiles and unsubscription events are processed in memory within the MCP Server's ephemeral V8 sandbox environments. No customer data is written to disk, and Vinkius manages the API tokens securely to keep them out of LLM prompts.

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