TNZ Communications MCP Server for LangChainGive LangChain instant access to 12 tools to Check Api Health, Create Tnz Contact, Get Account Balance, and more
LangChain is the leading Python framework for composable LLM applications. Connect TNZ Communications 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 App Connector for LangChain
The TNZ Communications app connector for LangChain is a standout in the Communication Messaging category — giving your AI agent 12 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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({
"tnz-communications": {
"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 TNZ Communications, 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 TNZ Communications MCP Server
Empower your AI agent with access to the TNZ Group messaging gateway to automate your SMS, Voice, and Fax communications in New Zealand and globally.
LangChain's ecosystem of 500+ components combines seamlessly with TNZ Communications through native MCP adapters. Connect 12 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
- Multichannel Messaging — Send SMS, automated voice calls (Text-to-Speech), and digital faxes programmatically.
- Delivery Oversight — Monitor the real-time status of sent messages and retrieve incoming SMS replies.
- Contact & Group Control — Manage your TNZ address book and organize contacts into groups for broadcast messaging.
- Operational Monitoring — Track your account credit balance and retrieve detailed messaging usage and cost reports.
The TNZ Communications MCP Server exposes 12 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.
All 12 TNZ Communications tools available for LangChain
When LangChain connects to TNZ Communications through Vinkius, your AI agent gets direct access to every tool listed below — spanning sms-gateway, voice-broadcasting, text-to-speech, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Verify TNZ API connectivity
Add a new contact to TNZ
Check account credit balance
Check delivery status of a message
Retrieve usage and cost reports
List your contact groups
List saved message templates
List inbound SMS replies
List saved contacts in TNZ
Send a document as a fax
Send an SMS message
Send a voice call (Text-to-Speech)
Connect TNZ Communications to LangChain via MCP
Follow these steps to wire TNZ Communications into LangChain. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install langchain langchain-mcp-adapters langgraph langchain-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
python agent.pyExplore tools
Why Use LangChain with the TNZ Communications MCP Server
LangChain provides unique advantages when paired with TNZ Communications through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine TNZ Communications 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 TNZ Communications queries for multi-turn workflows
TNZ Communications + LangChain Use Cases
Practical scenarios where LangChain combined with the TNZ Communications MCP Server delivers measurable value.
RAG with live data: combine TNZ Communications tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query TNZ Communications, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain TNZ Communications tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every TNZ Communications tool call, measure latency, and optimize your agent's performance
Example Prompts for TNZ Communications in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with TNZ Communications immediately.
"Send a SMS to +6421000000: 'The delivery is arriving at 2 PM today.'"
"What is the status of my message ID 'ref_123'?"
"Check my current TNZ account balance."
Troubleshooting TNZ Communications MCP Server with LangChain
Common issues when connecting TNZ Communications to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersTNZ Communications + LangChain FAQ
Common questions about integrating TNZ Communications 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.