How do I find my Bot ID?

Use the `list_bots` tool to see a comprehensive list of all bots in your account along with their unique IDs.

Can I see recent orders for a specific bot?

Yes, the `list_bot_orders` tool retrieves recent customer transactions and their current status for a target bot.

Is it possible to list subscribers via the agent?

Absolutely. Use the `list_bot_subscribers` tool with a bot ID to see the users who have interacted with your messenger bot.

Zenedu MCP Server for LangChain 6 tools — connect in under 2 minutes

Name: Zenedu
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 6 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Zenedu through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

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({
        "zenedu": {
            "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 Zenedu, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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* 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 Zenedu MCP Server

Connect your Zenedu account to any AI agent to automate your messenger marketing and sales funnels. This MCP server enables your agent to interact with bots, products, offers, and subscriber data directly.

LangChain's ecosystem of 500+ components combines seamlessly with Zenedu through native MCP adapters. Connect 6 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

Bot Oversight — List all your messenger bots and their associated metadata
Funnel Tracking — List and monitor sales funnels and automation flows for specific bots
Commerce Management — Access product catalogs and marketing offers synchronized with your bots
Order Visibility — Retrieve recent customer orders and transaction statuses
Audience Insight — List and query subscribers to track growth and engagement

The Zenedu MCP Server exposes 6 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 Zenedu to LangChain via MCP

Follow these steps to integrate the Zenedu 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 6 tools from Zenedu via MCP

Why Use LangChain with the Zenedu MCP Server

LangChain provides unique advantages when paired with Zenedu through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine Zenedu 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 Zenedu queries for multi-turn workflows

Zenedu + LangChain Use Cases

Practical scenarios where LangChain combined with the Zenedu MCP Server delivers measurable value.

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

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

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

Production monitoring: use LangSmith to trace every Zenedu tool call, measure latency, and optimize your agent's performance

Zenedu MCP Tools for LangChain (6)

These 6 tools become available when you connect Zenedu to LangChain via MCP:

list_bot_funnels

List all funnels for a specific bot

list_bot_offers

List all offers for a specific bot

list_bot_orders

List all orders for a specific bot

list_bot_products

List all products for a specific bot

list_bot_subscribers

List all subscribers for a specific bot

list_bots

List all messenger bots

Example Prompts for Zenedu in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with Zenedu immediately.

"List all messenger bots in my Zenedu account."

"Show me the funnels for bot ID '12345'."

"List recent orders for my 'Main Funnel' bot."

Troubleshooting Zenedu MCP Server with LangChain

Common issues when connecting Zenedu to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Zenedu + LangChain FAQ

Common questions about integrating Zenedu MCP Server with LangChain.

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.

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.