Mailjet MCP Server for Pydantic AI 8 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Mailjet 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 Mailjet "
"(8 tools)."
),
)
result = await agent.run(
"What tools are available in Mailjet?"
)
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 Mailjet MCP Server
Connect your Mailjet account to any AI agent to automate your transactional messaging and email marketing workflows. This MCP server enables your agent to send emails using the v3.1 Send API, manage subscriber lists, and track campaign performance directly from natural language interfaces.
Pydantic AI validates every Mailjet tool response against typed schemas, catching data inconsistencies at build time. Connect 8 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
- Transactional Delivery — Send single or batch emails with full support for HTML, attachments, and variables
- Audience Management — List all contacts, create new subscriber records, and manage contact lists (address books)
- Subscription Control — Add or remove contacts from specific lists and manage opt-in statuses programmatically
- Campaign Tracking — List historical campaigns and retrieve real-time performance statistics (opens, clicks, bounces)
- Metadata Oversight — Fetch detailed configuration and status for any campaign or subscriber collection
The Mailjet MCP Server exposes 8 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 Mailjet to Pydantic AI via MCP
Follow these steps to integrate the Mailjet 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 8 tools from Mailjet with type-safe schemas
Why Use Pydantic AI with the Mailjet MCP Server
Pydantic AI provides unique advantages when paired with Mailjet 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 Mailjet integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Mailjet connection logic from agent behavior for testable, maintainable code
Mailjet + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Mailjet MCP Server delivers measurable value.
Type-safe data pipelines: query Mailjet with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Mailjet tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Mailjet and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Mailjet responses and write comprehensive agent tests
Mailjet MCP Tools for Pydantic AI (8)
These 8 tools become available when you connect Mailjet to Pydantic AI via MCP:
add_contact_to_list
Requires list ID and contact ID/Email. Subscribe a contact to a specific list
create_new_contact
Requires at least an Email address. Add a new contact to the database
get_campaign_details
Get details for a specific campaign
get_campaign_performance
Get performance statistics for a campaign
list_all_contacts
List all contacts in the Mailjet account
list_marketing_campaigns
List all campaigns
list_subscriber_lists
List all contact lists
send_transactional_email
Requires a JSON body matching Mailjet v3.1 Send API structure. Send an email using Mailjet Send API v3.1
Example Prompts for Mailjet in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Mailjet immediately.
"Send a transactional email to 'passenger@example.com' with subject 'Boarding Pass'."
"List all active contact lists in my Mailjet account."
"Show performance stats for campaign ID '12345'."
Troubleshooting Mailjet MCP Server with Pydantic AI
Common issues when connecting Mailjet to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiMailjet + Pydantic AI FAQ
Common questions about integrating Mailjet 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 Mailjet 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 Mailjet to Pydantic AI
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.