Can I send WhatsApp messages using this server?

Yes. The `send_whatsapp_message` tool allows you to send outbound WhatsApp messages through the Vonage Messages API. You'll need a verified WhatsApp Business Number configured in your Vonage account as the sender.

How do I implement two-factor authentication (2FA)?

You can use the `start_verification` tool to send an OTP code to a user's phone. Once the user receives the code, use `check_verification_code` with the `request_id` to validate it. Your agent can handle the entire flow through a single conversation.

Can I check how much sending an SMS will cost me?

Absolutely. Use the `get_country_pricing` tool and provide the ISO country code (e.g., 'US' or 'GB'). Your agent will return the outbound SMS pricing for that region, helping you estimate costs before sending.

Vonage MCP Server for LangChain 10 tools — connect in under 2 minutes

Name: Vonage
Availability: InStock
Author: Vinkius

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

Built by Vinkius GDPR 10 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Vonage 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({
        "vonage": {
            "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 Vonage, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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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 Vonage MCP Server

Connect your Vonage account to any AI agent and power your global communications through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with Vonage through native MCP adapters. Connect 10 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

Multi-Channel Messaging — Send outbound messages via SMS, WhatsApp Business, and Viber with ease
2FA & Verification — Start and check identity verification requests (OTP) to secure your user accounts
Number Management — List all virtual phone numbers rented by your account and update their inbound webhooks
Account Insights — Check your real-time account credit balance and monitor spending directly from your agent
Global Pricing — Retrieve outbound SMS pricing for any country to estimate communication costs accurately
Virtual Numbers — View caller ID capabilities (SMS, Voice) for all your rented virtual numbers

The Vonage MCP Server exposes 10 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 Vonage to LangChain via MCP

Follow these steps to integrate the Vonage 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 10 tools from Vonage via MCP

Why Use LangChain with the Vonage MCP Server

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

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

Vonage + LangChain Use Cases

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

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

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

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

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

Vonage MCP Tools for LangChain (10)

These 10 tools become available when you connect Vonage to LangChain via MCP:

cancel_verification_request

Aborts an active verification request

check_verification_code

Checks the OTP code submitted by a user for an active verification request

get_account_balance

Retrieves the current Vonage account credit balance

get_country_pricing

Provide the ISO 3166-1 alpha-2 country code. Retrieves outbound SMS pricing for a specific country

list_rented_numbers

Lists all virtual phone numbers rented by the account

send_sms

Provide a sender name (alpha or number) and a target phone number in E.164 format. Sends an outbound SMS message via Vonage

send_viber_message

Provide your specific Viber Publisher ID. Sends a Viber service message via Vonage

send_whatsapp_message

Requires a verified WhatsApp Business Number as the sender. Sends a WhatsApp message via the Vonage Messages API

start_verification

Provide the target number and your brand name. Starts a 2FA identity verification by sending an OTP code

update_number_webhook

Requires the number in E.164 format. Updates the inbound SMS callback URL for a virtual number

Example Prompts for Vonage in LangChain

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

"Send an SMS to +123456789 saying 'Your order is ready for pickup!'."

"Start a verification for number +123456789 with brand 'MyCoolApp'."

"What is my current account balance and the SMS price for the UK?"

Troubleshooting Vonage MCP Server with LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Vonage + LangChain FAQ

Common questions about integrating Vonage 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.