MailWizz MCP Server for Pydantic AI 9 tools — connect in under 2 minutes
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.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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())
* 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.
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 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.
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 MailWizz integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
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.
Type-safe data pipelines: query MailWizz with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple MailWizz tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query MailWizz and output structured, schema-compliant notifications
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:
add_subscriber_to_list
Requires a list UID and subscriber data. Add a new subscriber to a list
delete_list_subscriber
Remove a subscriber from a list
get_campaign_details
Get details for a specific campaign
get_list_details
Get details for a specific subscriber list
list_email_campaigns
List all email marketing campaigns
list_list_subscribers
List subscribers in a specific list
list_subscriber_collections
List all subscriber lists
pause_email_campaign
Pause a running campaign
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.
"List all active email campaigns in MailWizz."
"Add 'user@example.com' to my 'Main Leads' list (UID: 'lz987xyz')."
"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.
MCPServerHTTP not found
pip install --upgrade pydantic-aiMailWizz + Pydantic AI FAQ
Common questions about integrating MailWizz MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
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?
Can I switch LLM providers without changing MCP code?
Connect MailWizz with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
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.
