2Chat MCP Server for LangChain 5 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect 2Chat through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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({
"2chat": {
"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 2Chat, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
asyncio.run(main())
* 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 2Chat MCP Server
Unlock the full potential of WhatsApp automation with 2Chat, the programmable gateway now integrated with your AI agent. By connecting 2Chat via the Model Context Protocol, you transcend the limitations of traditional messaging apps. Your agent can now orchestrate complex group workflows, verify phone numbers before sending, and manage multi-device communications through simple natural language. Whether you're coordinating team alerts or engaging with a community, 2Chat gives your AI the 'voice' it needs on the world's most popular messaging platform.
LangChain's ecosystem of 500+ components combines seamlessly with 2Chat through native MCP adapters. Connect 5 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
- Programmable Messaging — Send text, images, PDF, and voice messages to any WhatsApp number without template restrictions.
- Group Management — Create groups, add participants, and send group-wide announcements directly from your chat interface.
- Number Verification — Check if a phone number is registered on WhatsApp before sending to improve delivery success.
- Webhooks & Real-time — Monitor incoming messages and delivery status (sent, delivered, read) seamlessly.
- Multi-Device Support — Link multiple WhatsApp numbers to a single API workspace for unified communications.
The 2Chat MCP Server exposes 5 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 2Chat to LangChain via MCP
Follow these steps to integrate the 2Chat 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 5 tools from 2Chat via MCP
Why Use LangChain with the 2Chat MCP Server
LangChain provides unique advantages when paired with 2Chat through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine 2Chat 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 2Chat queries for multi-turn workflows
2Chat + LangChain Use Cases
Practical scenarios where LangChain combined with the 2Chat MCP Server delivers measurable value.
RAG with live data: combine 2Chat tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query 2Chat, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain 2Chat tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every 2Chat tool call, measure latency, and optimize your agent's performance
2Chat MCP Tools for LangChain (5)
These 5 tools become available when you connect 2Chat to LangChain via MCP:
check_number
Helps prevent failed delivery errors. Verify if a phone number is registered on WhatsApp
create_group
Create a new WhatsApp group with specified participants
list_groups
List all WhatsApp groups that a connected number belongs to
list_numbers
Use this to identify which "from_number" to use in subsequent sending actions. List all WhatsApp phone numbers connected to your 2Chat account
send_message
Can send text or public URL media to direct numbers or a specific group UUID. Send a WhatsApp text or media message using a connected number
Example Prompts for 2Chat in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with 2Chat immediately.
"Check if +123456789 is registered on WhatsApp and send a message saying hello."
"List all my WhatsApp groups."
"Create a new WhatsApp group called 'Project Gamma' and add participant +198765432."
Troubleshooting 2Chat MCP Server with LangChain
Common issues when connecting 2Chat to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adapters2Chat + LangChain FAQ
Common questions about integrating 2Chat MCP Server with LangChain.
How does LangChain connect to MCP servers?
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?
Can I trace MCP tool calls in LangSmith?
Connect 2Chat with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect 2Chat to LangChain
Get your token, paste the configuration, and start using 5 tools in under 2 minutes. No API key management needed.