Brevo MCP Server for LangChainGive LangChain instant access to 11 tools to Create Contact, Create Email Campaign, Get Account, and more
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.
Ask AI about this App Connector for LangChain
The Brevo app connector for LangChain is a standout in the Marketing Automation category — giving your AI agent 11 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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-alternative": {
"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())
* 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 account to any AI agent and take full control of your marketing automation and transactional communication workflows through natural conversation.
LangChain's ecosystem of 500+ components combines seamlessly with Brevo through native MCP adapters. Connect 11 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
- Contact Orchestration — List and manage your contact database programmatically, retrieving detailed high-fidelity profiles and synchronizing custom attributes in real-time
- Campaign Intelligence — Create and monitor high-fidelity email marketing campaigns and retrieve detailed performance reports directly through your agent
- Transactional Messaging — Programmatically dispatch single transactional emails via Brevo SMTP to ensure perfectly coordinated customer notifications
- Audience Discovery — Access complete directories of contact lists and manage segmentations to maintain high-fidelity targeting for your digital outreach
- Operational Monitoring — Access account-level metadata, verified senders, and real-time SMTP delivery statistics for instant operational reporting
The Brevo MCP Server exposes 11 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.
All 11 Brevo tools available for LangChain
When LangChain connects to Brevo through Vinkius, your AI agent gets direct access to every tool listed below — spanning sms-marketing, transactional-email, contact-management, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Create a new contact
Create an email campaign
Get Brevo account details
Get details for a specific contact
Get details for a specific list
Get SMTP delivery statistics
List contact lists
List Brevo contacts
List email campaigns
List approved senders
Send a transactional email
Connect Brevo to LangChain via MCP
Follow these steps to wire Brevo into LangChain. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install langchain langchain-mcp-adapters langgraph langchain-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
python agent.pyExplore tools
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
Example Prompts for Brevo in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Brevo immediately.
"List all active contacts in my Brevo database."
"Send a transactional email to 'test@example.com' with subject 'Order Confirmed'."
"Show my email campaign engagement statistics."
Troubleshooting Brevo MCP Server with LangChain
Common issues when connecting Brevo to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersBrevo + LangChain FAQ
Common questions about integrating Brevo MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.