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 LangChain 10 tools — connect in under 2 minutes

Name: Brevo
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Brevo through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

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 langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "brevo": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Brevo, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

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.

LangChain's ecosystem of 500+ components combines seamlessly with Brevo through native MCP adapters. Connect 10 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

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 LangChain 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 LangChain via MCP

Follow these steps to integrate the Brevo MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 10 tools from Brevo via MCP

Why Use LangChain with the Brevo MCP Server

LangChain provides unique advantages when paired with Brevo through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine Brevo MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across Brevo queries for multi-turn workflows

Brevo + LangChain Use Cases

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

RAG with live data: combine Brevo tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Brevo, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Brevo tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Brevo tool call, measure latency, and optimize your agent's performance

Brevo MCP Tools for LangChain (10)

These 10 tools become available when you connect Brevo to LangChain 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 LangChain

Ready-to-use prompts you can give your LangChain 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 LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Brevo + LangChain FAQ

Common questions about integrating Brevo MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.