Can I format the transactional emails organically via prompt?

Absolutely. Using the `send_transactional_email` operation, the AI dynamically renders the HTML body from your specific text instructions or leverages pre-made numeric Brevo templates.

Is it possible to assign custom CRM attributes when creating a contact?

Yes. The `create_contact` tool exposes a JSON parameter block mapping fields perfectly (like FIRSTNAME, LASTNAME, CITY) directly alongside their assigned inclusion lists.

Are the SMS dispatched globally?

Yes! Brevo's massive routing handles global cellular numbers, and the `send_sms` command executes that payload identically as long as your Brevo account remains credit-funded and active.

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

Name: Brevo
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 Brevo through the 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 Brevo "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Brevo?"
    )
    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 Brevo MCP Server

Connect your Brevo (formerly Sendinblue) account to any AI agent and execute marketing operations and crucial transactional workflows via natural conversation.

Pydantic AI validates every Brevo tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through the 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 Emails — Send richly formatted HTML or template-based alerts instantly on demand
SMS Dispatch — Fire immediate SMS campaigns and notifications globally to verified phone numbers
Contacts & CRM — Seamlessly create new user profiles, map attributes, and assign lists structurally

The Brevo 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 Brevo to Pydantic AI via MCP

Follow these steps to integrate the Brevo 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 Brevo with type-safe schemas

Why Use Pydantic AI with the Brevo MCP Server

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

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

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

Brevo + Pydantic AI Use Cases

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

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

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

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

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

Brevo MCP Tools for Pydantic AI (10)

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

create_contact_list

Create a new empty audience list folder for organizing campaigns in Brevo

create_crm_contact

Create a new contact record within the Brevo CRM

delete_crm_contact

Permanently delete a CRM contact profile conforming to database compliance

get_contact_attributes

Retrieve specific profile attributes and metadata for a given contact email

get_smtp_account_details

Retrieve the current Brevo account status, plans, and quota mappings

list_contact_folders

Retrieve all contact lists and campaign segments structured in the CRM

list_crm_contacts

List all contacts stored in the Brevo CRM

send_transactional_email

Needs absolute mapped verified domains to avoid DKIM failure bouncing. Send a transactional email payload via the Brevo SMTP API

send_transactional_sms

164 phone formats via `/transactionalSMS/sms` successfully bypassing web clients. Dispatch an automated transactional SMS directly to cellular hardware

update_contact_attributes

Update custom attributes or metadata parameters for a specific CRM contact

Example Prompts for Brevo in Pydantic AI

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

"Send a transactional email to test@domain.com saying hello."

"Create contact john.doe@mail.com and map their name as John."

"Can you text message 'Server requires reboot' to my admin phone?"

Troubleshooting Brevo MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Brevo + Pydantic AI FAQ

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