How to Use the Mailjet MCP in LangChain
Chain Mailjet's delivery API directly into your LangChain agents for automated email routing and list management.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Mailjet MCP to LangChain
Create your Vinkius account to connect Mailjet 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.
Sequential Email Operations in LangChain
Your ReAct agent can execute `create_new_contact` and immediately chain the output into list assignment. It grabs user data, fires off the first request, and passes the resulting ID directly into `add_contact_to_list`. No manual sync required. LangSmith tracks every step of this pipeline. You see the exact payload sent to `send_transactional_email` and how long the API took to respond. If a step fails, the agent reads the error and retries with corrected JSON.
Fetch and Evaluate Campaign Data
Feed campaign performance directly into your reporting pipelines by executing `list_marketing_campaigns`. The agent grabs active campaign IDs, then maps those into `get_campaign_performance` to pull open rates and click data. You do not have to write custom polling loops. The MCP Server handles the REST abstraction while your LangChain setup decides what to do with the metrics. Route bad numbers to Slack or trigger a follow-up sequence based on the results.
Autonomous Subscriber Sync via MCP Server
Keep your CRM and Mailjet lists identical by letting your agent run `list_all_contacts` via the MCP Server. It compares the raw output against your internal database to spot missing users. When it finds a discrepancy, it calls `list_subscriber_lists` to find the correct segment. It then executes the updates autonomously. You just set the rules in your LangGraph nodes and let the system run.
Set up Mailjet MCP in LangChain
Prerequisites
- Python 3.10+ installed
-
langchain-mcp-adapters+langgraphpackages - 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 LangChainBaseToolobjects. - 2
Connect via HTTP transport
Use
MultiServerMCPClientwith"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 Mailjet tool calls through the MCP protocol. - 4
Run with any LLM
Swap
ChatOpenAIforChatAnthropic,ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.
from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI
async with MultiServerMCPClient({
"mailjet-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 Mailjet transactions"
})
print(result["messages"][-1].content) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Mailjet. 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.
Why Choose Vinkius
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visibility into every interaction
Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.
Built-in savings
60%
lower AI costs
Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.
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place for every integration
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Common questions about Mailjet MCP in LangChain
Use it with your favorite AI tools
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