How to Use the Gupshup Messaging MCP in LangChain

Q: Does the server support interactive messages?

It does. You use sendinteractivemessage to include button arrays in your messages, which LangChain agents can generate based on user context.

Build complex messaging pipelines in LangChain by chaining Gupshup Messaging tools for automated WhatsApp workflows.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Gupshup Messaging MCP to LangChain

Create your Vinkius account to connect Gupshup Messaging 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.

GDPR Free for Subscribers

Setup Gupshup Messaging with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Chain WhatsApp actions in LangChain

Connect `send_text_message` and `send_template_message` directly into your LangGraph nodes. The agent evaluates the state and triggers the next step in your sequence automatically. This setup removes manual intervention. You define the logic, and the server executes each call as a distinct link in the chain.

Automated media and reaction handling

Use `send_media_message` to push files into your chains based on runtime conditions. You can follow up with `send_reaction` to confirm receipt within the same execution path. Observability is native through your existing tracing tools. Every payload is logged, giving you a clear view of how messages flow through your agent.

Template management for dynamic agents

Fetch metadata using `get_template_info` before deciding which template to dispatch. Your agent checks the requirements first, preventing API errors before they happen. This keeps your communication consistent. The agent handles the parameter injection, ensuring your messages always align with approved WhatsApp formats.

Setup guide

Set up Gupshup Messaging 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 Gupshup Messaging 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({
    "gupshup-messaging-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 Gupshup Messaging transactions"
    })
    print(result["messages"][-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Gupshup. 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

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Gupshup Messaging now

Real-time monitoring

Live

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.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Gupshup Messaging MCP in LangChain

You install the MCP adapters and point your client to the server URL. Once configured, you pull the tool list into your agent constructor to start sending messages.

Yes, you connect the tool output to your agent's reasoning loop. The agent processes incoming data and decides when to trigger a message using the available tools.

It provides the direct interface for WhatsApp API calls. You should wrap these tools in your own retry logic to handle potential network fluctuations during high-volume periods.

It does. You use `send_interactive_message` to include button arrays in your messages, which LangChain agents can generate based on user context.

Your API credentials and message payloads are processed in memory during the request. The server does not store your WhatsApp contact data or message logs locally.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript