How do I get a MoonMail API Key?

Log in to MoonMail and navigate to Settings > API Keys to generate your key. This token is required for all API operations.

Can I send a campaign through this server?

Yes! Use the `send_campaign` tool with a valid Campaign ID to trigger the delivery process.

How do I see how many people opened my email?

Use the `get_campaign_stats` tool with the Campaign ID to retrieve the open rate, click rate, and other engagement metrics.

MoonMail MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: MoonMail
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect MoonMail 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 MoonMail "
            "(10 tools)."
        ),
    )

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

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 MoonMail MCP Server

Connect your MoonMail account to your AI agent and optimize your email marketing operations through natural conversation.

Pydantic AI validates every MoonMail tool response against typed schemas, catching data inconsistencies at build time. Connect 10 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 Management — List all email campaigns, create new ones, and trigger delivery to your audience.
Subscriber Growth — Access your subscriber lists, add new contacts, and manage audience segments.
Engagement Insights — Monitor real-time performance metrics (opens, clicks) and tracking events for your campaigns.
Recipients Tracking — Fetch the list of all individual recipients for specific campaign IDs.
List Oversight — View all mailing lists and their current subscriber counts to stay organized.

The MoonMail MCP Server exposes 10 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 MoonMail to Pydantic AI via MCP

Follow these steps to integrate the MoonMail 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 10 tools from MoonMail with type-safe schemas

Why Use Pydantic AI with the MoonMail MCP Server

Pydantic AI provides unique advantages when paired with MoonMail 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 MoonMail integration code

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

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

MoonMail + Pydantic AI Use Cases

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

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

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

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

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

MoonMail MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect MoonMail to Pydantic AI via MCP:

add_subscriber

Add a subscriber to a list

create_campaign

Create a new email campaign

get_campaign_stats

Get campaign performance metrics

get_events

Get email analytics events

list_campaign_recipients

List recipients of a campaign

list_campaigns

List MoonMail campaigns

list_lists

List subscriber lists

list_segments

List audience segments

list_subscribers

List members of a list

send_campaign

Send an email campaign

Example Prompts for MoonMail in Pydantic AI

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

"List all my email campaigns and their status."

"How is my 'New Feature Announcement' campaign performing?"

"Add alex@example.com to the 'VIP Customers' list."

Troubleshooting MoonMail MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

MoonMail + Pydantic AI FAQ

Common questions about integrating MoonMail 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 MoonMail MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.