How do I enable the Mautic API?

Go to Mautic Settings > Configuration > API Settings and set 'API Enabled?' to 'Yes'. Also enable 'HTTP Basic Auth' for this integration.

Can I search for contacts by email?

Yes! Use the `list_contacts` tool and provide the email address in the search parameter.

Is my Mautic data secure?

Absolutely. Your credentials are encrypted at rest and injected securely at runtime.

Mautic MCP Server for Pydantic AI 11 tools — connect in under 2 minutes

Name: Mautic
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 11 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Mautic through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Mautic "
            "(11 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Mautic?"
    )
    print(result.data)

asyncio.run(main())

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Mautic MCP Server

Connect your Mautic marketing automation instance to any AI agent and take full control of your marketing workflows through natural conversation.

Pydantic AI validates every Mautic tool response against typed schemas, catching data inconsistencies at build time. Connect 11 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Contact Management — Search for contacts, fetch detailed profiles, and create new records on the fly
Campaign Tracking — List and inspect marketing automation campaigns and their configurations
Email Marketing — Manage email templates and retrieve details for specific marketing emails
Audience Segmentation — List contact segments and add contacts to specific lists for targeted marketing
Company Data — Manage company (account) records and their associations within Mautic

The Mautic MCP Server exposes 11 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Mautic to Pydantic AI via MCP

Follow these steps to integrate the Mautic MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 11 tools from Mautic with type-safe schemas

Why Use Pydantic AI with the Mautic MCP Server

Pydantic AI provides unique advantages when paired with Mautic through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Mautic integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Mautic connection logic from agent behavior for testable, maintainable code

Mautic + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Mautic MCP Server delivers measurable value.

Type-safe data pipelines: query Mautic with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Mautic tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Mautic and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Mautic responses and write comprehensive agent tests

Mautic MCP Tools for Pydantic AI (11)

These 11 tools become available when you connect Mautic to Pydantic AI via MCP:

add_contact_to_segment

Add a contact to a segment

create_contact

Create a new contact

get_campaign

Get campaign details by ID

get_company

Get company details by ID

get_contact

Get a specific contact by ID

get_email

Get email details by ID

list_campaigns

List all campaigns

list_companies

List all companies

list_contacts

Supports an optional search query. List or search contacts

list_emails

List all email templates

list_segments

List all contact segments

Example Prompts for Mautic in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Mautic immediately.

"Find contact info for john.doe@example.com in Mautic."

"List all active marketing campaigns."

"Add contact ID 1234 to segment ID 5."

Troubleshooting Mautic MCP Server with Pydantic AI

Common issues when connecting Mautic to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Mautic + Pydantic AI FAQ

Common questions about integrating Mautic MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Mautic MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.