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MailWizz MCP Server for Pydantic AI 9 tools — connect in under 2 minutes

Built by Vinkius GDPR 9 Tools SDK

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

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 MailWizz "
            "(9 tools)."
        ),
    )

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

asyncio.run(main())
MailWizz
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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 MailWizz MCP Server

Connect your MailWizz instance to any AI agent to automate your professional email marketing and audience management. This MCP server enables your agent to manage subscriber lists, control campaign lifecycles, and update subscriber data directly from natural language interfaces.

Pydantic AI validates every MailWizz tool response against typed schemas, catching data inconsistencies at build time. Connect 9 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

  • Campaign Oversight — List all email campaigns and retrieve detailed metadata and status information
  • Mailing Control — Pause or unpause campaigns and manage their delivery lifecycle programmatically
  • Audience Management — List all subscriber collections (lists) and retrieve their unique identifiers
  • Subscriber Administration — Add, update, and remove subscribers from specific lists using their UIDs
  • Data Ingestion — Sync subscriber information and manage custom fields across your email databases
  • Self-Hosted Support — Works with any self-hosted MailWizz instance using your personal API keys

The MailWizz MCP Server exposes 9 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 MailWizz to Pydantic AI via MCP

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

01

Install Pydantic AI

Run pip install pydantic-ai

02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

03

Run the agent

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

04

Explore tools

The agent discovers 9 tools from MailWizz with type-safe schemas

Why Use Pydantic AI with the MailWizz MCP Server

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

01

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

02

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

03

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

04

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

MailWizz + Pydantic AI Use Cases

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

01

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

02

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

03

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

04

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

MailWizz MCP Tools for Pydantic AI (9)

These 9 tools become available when you connect MailWizz to Pydantic AI via MCP:

01

add_subscriber_to_list

Requires a list UID and subscriber data. Add a new subscriber to a list

02

delete_list_subscriber

Remove a subscriber from a list

03

get_campaign_details

Get details for a specific campaign

04

get_list_details

Get details for a specific subscriber list

05

list_email_campaigns

List all email marketing campaigns

06

list_list_subscribers

List subscribers in a specific list

07

list_subscriber_collections

List all subscriber lists

08

pause_email_campaign

Pause a running campaign

09

update_list_subscriber

Update an existing subscriber

Example Prompts for MailWizz in Pydantic AI

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

01

"List all active email campaigns in MailWizz."

02

"Add 'user@example.com' to my 'Main Leads' list (UID: 'lz987xyz')."

03

"Pause the email campaign with UID 'cp456def'."

Troubleshooting MailWizz MCP Server with Pydantic AI

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

01

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

MailWizz + Pydantic AI FAQ

Common questions about integrating MailWizz MCP Server with Pydantic AI.

01

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.
02

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.
03

Can I switch LLM providers without changing MCP code?

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

Connect MailWizz to Pydantic AI

Get your token, paste the configuration, and start using 9 tools in under 2 minutes. No API key management needed.