How to Use the Gallabox MCP in LangChain

Q: Can I trace Gallabox message delivery inside LangSmith?

Yes, every time LangChain calls sendwhatsapptext via the MCP Server, LangSmith logs the payload and response. You see the exact delivery status and latency of your WhatsApp messages in the tracing dashboard.

Build multi-step WhatsApp messaging chains in LangChain with this Gallabox MCP Server to automate customer threads.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Gallabox MCP to LangChain

Create your Vinkius account to connect Gallabox 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 Gallabox with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Chain WhatsApp templates into LangChain agents

The `send_whatsapp_template` and `list_message_templates` tools let your LangChain ReAct agent select approved templates and dispatch them based on live conversation states. Your agent checks the template registry first, pulls the correct parameters, and fires off the message without manual intervention. LangSmith traces every step of this template execution, exposing latency and exact token costs for each API call. You see exactly when the agent chooses to send a template versus when it falls back to custom text.

Trace live WhatsApp thread triage in LangGraph

The `list_active_chats` and `get_chat_details` tools pull live thread metadata directly into your LangGraph state graph. Your pipeline uses this metadata to route incoming WhatsApp messages to specific support queues based on customer history. This setup eliminates manual routing by feeding live chat states directly into your decision chains. You monitor the entire routing logic inside LangSmith to debug why an agent sent a thread to a specific team.

Feed active contact data to LangChain tools

The `list_whatsapp_contacts` and `get_contact_details` tools pull customer profiles directly into your LangChain agent's working memory. Your agent uses this contact data to personalize automated replies or update external CRM systems mid-chain. By combining these MCP tools with databases or vector stores in the same chain, your agent maintains context across multiple sessions. You build complex, stateful loops that keep WhatsApp contacts updated without hardcoding API calls.

Setup guide

Set up Gallabox 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 Gallabox 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({
    "gallabox-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 Gallabox 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 Gallabox. 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 Gallabox 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 Gallabox MCP in LangChain

LangChain manages this through custom runnables or rate-limiting wrappers around the MCP tools. If you hit Gallabox API limits, the chain pauses and retries based on your backoff policy.

Yes, every time LangChain calls `send_whatsapp_text` via the MCP Server, LangSmith logs the payload and response. You see the exact delivery status and latency of your WhatsApp messages in the tracing dashboard.

You use the MultiServerMCPClient to aggregate this MCP Server with your database or CRM tools. LangChain agents then query both sources to compose personalized WhatsApp replies.

You pass your endpoint token to the Vinkius managed client configuration during setup. The server handles the underlying API headers so your LangChain code stays clean.

The server processes contact details and message histories in an ephemeral V8 sandbox that wipes clean after execution. Your customer phone numbers and chat logs never persist on Vinkius servers.

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