How to Use the Brevo MCP in Pydantic AI

Strictly typed marketing automation for Pydantic AI with this MCP server.

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Connect Brevo MCP to Pydantic AI

Create your Vinkius account to connect Brevo to Pydantic AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Brevo with Pydantic AI

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Validate Brevo contacts in Pydantic AI

Every response from `get_contact` is checked against your defined models. Pydantic AI rejects any data that doesn't match your schema. This prevents your agent from processing malformed records. You get clean, predictable data every time.

Create contacts with Pydantic AI

Use the `create_contact` tool to push new leads into your database. The framework ensures all fields meet your formatting requirements. If the input is wrong, the agent throws a validation error immediately. This keeps your records accurate without manual cleanup.

List campaigns in Pydantic AI

Retrieve active campaigns using `list_email_campaigns` and map them to your internal objects. This makes your agent aware of past and current activity. The type-safe approach ensures you always know what fields are available. It removes guesswork from your agent's logic.

Setup guide

Set up Brevo MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "brevo-alternative-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Brevo tools.",
)

result = await agent.run("List recent Brevo transactions")
print(result.output)

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Why Choose Vinkius

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Common questions about Brevo MCP in Pydantic AI

Instantiate the MCPToolset with your Vinkius URL. Pass it into your agent's list of toolsets to start executing operations.

Yes. Every tool response is parsed into a Pydantic model at runtime. If the Brevo API returns unexpected data, the agent crashes before acting on it.

It supports both Streamable HTTP and SSE transports. You just need to specify the correct protocol in your toolset initialization.

You get the reliability of strict typing for your marketing data. It prevents the agent from hallucinating fields that don't exist in your account.

The server runs externally and handles your requests through a secure tunnel. Your contact email lists and campaign details are never cached on the Vinkius platform.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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