How to Use the Brevo MCP in LangChain

Q: How do I handle Brevo rate limits in a LangChain chain?

You can use LangChain's retry parsers alongside the getsmtpaccountdetails tool to check your monthly Brevo quotas. If your LangChain agent detects a near-limit state, it can pause execution or alert your admin team.

Q: Can LangChain agents delete Brevo contacts using this MCP Server?

Yes, they can. Your LangChain agent uses deletecrmcontact to remove profiles when a user requests deletion. This helps you maintain compliance directly inside your autonomous LangChain workflows.

Q: How do I pass Brevo MCP tools to a LangChain agent?

Install langchain-mcp-adapters and use the MultiServerMCPClient to connect to the Vinkius endpoint. Retrieve the Brevo tools with client.gettools() and pass them directly to your LangChain agent's initialization step.

Q: How does LangSmith help debug Brevo email failures?

LangSmith records the exact input payloads passed to sendtransactionalemail. If a Brevo email bounces due to a bad domain, you can inspect the raw JSON arguments in your LangSmith dashboard to fix the formatting.

Run multi-step marketing workflows using Brevo tools directly inside your LangChain reasoning pipelines.

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Connect Brevo MCP to LangChain

Create your Vinkius account to connect Brevo to LangChain 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 LangChain

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Sync CRM contacts across LangChain chains

The `create_crm_contact` tool lets your LangChain agent write new records directly into your Brevo CRM during active runs. When a LangChain user submits an inquiry, the agent extracts their details and immediately inserts them into your Brevo marketing pipeline. By chaining this with `update_contact_attributes` in LangGraph, your agent updates Brevo lead scores based on conversation context. LangSmith traces every step, so you see exactly how the agent mapped the incoming payload to your Brevo fields.

Trigger transactional emails via LangChain agents

The `send_transactional_email` tool gives your LangChain agent the ability to shoot out verified Brevo notifications based on run outcomes. If a LangChain chain detects a critical event, it instantly fires off an email through this MCP Server to keep your team informed. Because this requires verified domains to prevent bounces, your LangChain chain can run pre-flight checks. It uses `get_smtp_account_details` to verify Brevo quota limits before attempting to push the message out.

Manage Brevo contact folders in LangChain

The `create_contact_list` tool allows your LangChain pipeline to dynamically segment users into Brevo folders based on their interactions. When a LangChain user changes their preferences, the agent runs this tool to sort them into the right bucket. You can combine this with `list_contact_folders` to scan existing Brevo groups before creating duplicates in your LangChain workflow. This keeps your Brevo marketing lists clean and ensures your automated campaigns target the right people every time.

Setup guide

Set up Brevo MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes Brevo tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

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

async with MultiServerMCPClient({
    "brevo-mcp": {
        "transport": "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,
    )
    result = await agent.ainvoke({
        "messages": "List recent Brevo transactions"
    })
    print(result["messages"][-1].content)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Brevo. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Brevo MCP in LangChain

You can use LangChain's retry parsers alongside the `get_smtp_account_details` tool to check your monthly Brevo quotas. If your LangChain agent detects a near-limit state, it can pause execution or alert your admin team.

Yes, they can. Your LangChain agent uses `delete_crm_contact` to remove profiles when a user requests deletion. This helps you maintain compliance directly inside your autonomous LangChain workflows.

Install `langchain-mcp-adapters` and use the `MultiServerMCPClient` to connect to the Vinkius endpoint. Retrieve the Brevo tools with `client.get_tools()` and pass them directly to your LangChain agent's initialization step.

LangSmith records the exact input payloads passed to `send_transactional_email`. If a Brevo email bounces due to a bad domain, you can inspect the raw JSON arguments in your LangSmith dashboard to fix the formatting.

Vinkius runs the server in an isolated sandbox, ensuring your Brevo contact lists and email addresses are never exposed to other LangChain runs. Only the specific CRM payloads passed to `update_contact_attributes` or `create_crm_contact` are processed during the active LangChain session.

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