How to Use the Mautic MCP in Pydantic AI

Q: How do I connect Pydantic AI to the Mautic MCP Server?

Install the package with pip install "pydantic-ai-slimmcp". Use the MCPToolset class pointing to your Vinkius HTTP endpoint, and pass it to your Agent via the toolsets parameter.

Q: How is my contact segment data protected during validation?

Your segment lists fetched via listsegments are validated in memory on your host machine. Vinkius handles the API transit through a secure, isolated sandbox, ensuring your customer database remains private.

Build type-safe marketing workflows with Pydantic AI validating every Mautic API response at runtime.

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Connect Mautic MCP to Pydantic AI

Create your Vinkius account to connect Mautic 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 Mautic with Pydantic AI

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Type-safe lead creation with Pydantic AI

Stop worrying about malformed contact records breaking your database. Your agent uses `create_contact` and `get_contact` with strict Pydantic schemas validating the structure before any write occurs. If the API returns unexpected fields, the framework raises a validation error immediately. This prevents silent database corruption and ensures your sales team always gets clean lead data.

Runtime-validated segment management

Manage your contact lists without trusting the model to guess field types. Your agent queries `list_segments` and adds users via `add_contact_to_segment` using strictly typed models. The agent matches contacts from `list_contacts` against your validation schemas. If a contact is missing a required email or phone field, the agent flags it instead of failing silently mid-run.

Guaranteed schema compliance for MCP Server actions

Fetch campaigns and emails knowing the data structure is guaranteed. This MCP Server maps tools like `get_campaign` and `list_campaigns` directly to Python classes, giving you autocomplete in your editor. You get the same type-safety for email templates retrieved via `get_email` and `list_emails`. Your agent can safely inspect template HTML and body text, confident that the payload matches your code's expectations.

Setup guide

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

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

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

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Common questions about Mautic MCP in Pydantic AI

Install the package with `pip install "pydantic-ai-slim[mcp]"`. Use the `MCPToolset` class pointing to your Vinkius HTTP endpoint, and pass it to your Agent via the `toolsets` parameter.

Pydantic AI will raise a validation error at runtime. This prevents your agent from acting on corrupt or incomplete contact records fetched via `get_contact`.

Yes, you can use any LLM provider with this setup. The type validation happens in Python, so your agent remains stable whether you use OpenAI, Anthropic, or local models.

The framework expects the server to run externally. You can host it on Vinkius and connect via the streamable HTTP transport, keeping your local environment clean.

Your segment lists fetched via `list_segments` are validated in memory on your host machine. Vinkius handles the API transit through a secure, isolated sandbox, ensuring your customer database remains private.

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