Convertlab MCP Server for LangChain 8 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Convertlab 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 MCP SERVER
Vinkius supports streamable HTTP and SSE.
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({
"convertlab": {
"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 Convertlab, 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 Convertlab MCP Server
Empower your AI agent to orchestrate your marketing operations with Convertlab (DM Hub), the leading customer engagement and marketing automation platform in China. By connecting Convertlab to your agent, you transform complex customer segmentation, campaign tracking, and behavioral auditing into a natural conversation. Your agent can instantly list customers, retrieve detailed profile information, monitor marketing campaigns, and browse behavioral events without you ever needing to navigate the comprehensive DM Hub interface. Whether you are conducting a customer data audit or monitoring the performance of a high-volume campaign, your agent acts as a real-time marketing operations assistant, keeping your data accurate and your engagement moving.
LangChain's ecosystem of 500+ components combines seamlessly with Convertlab through native MCP adapters. Connect 8 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
- Customer Orchestration — List all DM Hub customers and retrieve detailed profile and membership information.
- Campaign Management — Browse active and historical marketing campaigns and retrieve detailed performance metadata.
- Event Auditing — List and retrieve detailed customer behavioral events to monitor engagement levels.
- Segmentation Control — Browse membership groups and identify customer segments for targeted activities.
- Operations Insights — Retrieve metadata about your marketing touchpoints and application status.
The Convertlab MCP Server exposes 8 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 Convertlab to LangChain via MCP
Follow these steps to integrate the Convertlab 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 8 tools from Convertlab via MCP
Why Use LangChain with the Convertlab MCP Server
LangChain provides unique advantages when paired with Convertlab through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Convertlab 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 Convertlab queries for multi-turn workflows
Convertlab + LangChain Use Cases
Practical scenarios where LangChain combined with the Convertlab MCP Server delivers measurable value.
RAG with live data: combine Convertlab tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Convertlab, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Convertlab tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Convertlab tool call, measure latency, and optimize your agent's performance
Convertlab MCP Tools for LangChain (8)
These 8 tools become available when you connect Convertlab to LangChain via MCP:
create_customer
Create a new customer
get_campaign
Get campaign details
get_customer
Get customer details
list_campaigns
List marketing campaigns
list_customers
List DM Hub customers
list_events
List marketing events
list_member_groups
List customer segments
list_touchpoints
List marketing touchpoints
Example Prompts for Convertlab in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Convertlab immediately.
"List all my DM Hub customers."
"Show me the details for campaign 'Spring-2026'."
"List all customer segmentation groups."
Troubleshooting Convertlab MCP Server with LangChain
Common issues when connecting Convertlab to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersConvertlab + LangChain FAQ
Common questions about integrating Convertlab 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.Which LangChain agent types work with MCP?
Can I trace MCP tool calls in LangSmith?
Connect Convertlab with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Convertlab to LangChain
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.
