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Convertlab MCP Server for LangChain 8 tools — connect in under 2 minutes

Built by Vinkius GDPR 8 Tools Framework

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.

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({
        "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())
Convertlab
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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 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.

01

Install dependencies

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

02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

03

Run the agent

Save the code and run python agent.py

04

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.

01

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

02

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

03

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

04

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.

01

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

02

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

03

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

04

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:

01

create_customer

Create a new customer

02

get_campaign

Get campaign details

03

get_customer

Get customer details

04

list_campaigns

List marketing campaigns

05

list_customers

List DM Hub customers

06

list_events

List marketing events

07

list_member_groups

List customer segments

08

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.

01

"List all my DM Hub customers."

02

"Show me the details for campaign 'Spring-2026'."

03

"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.

01

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Convertlab + LangChain FAQ

Common questions about integrating Convertlab MCP Server with LangChain.

01

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.
02

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.
03

Can I trace MCP tool calls in LangSmith?

Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.

Connect Convertlab to LangChain

Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.