How to Use the Dexatel MCP in LangChain

Q: How do I connect the Dexatel MCP Server to LangChain?

Install the langchain-mcp-adapters package. Initialize a MultiServerMCPClient pointing to your Vinkius endpoint, call client.gettools(), and pass that array to your agent constructor.

Build ReAct agents that send SMS and track delivery chains with Dexatel and LangChain.

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Connect Dexatel MCP to LangChain

Create your Vinkius account to connect Dexatel 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.

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Setup Dexatel with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Orchestrate SMS Dispatch Chains via MCP Server

LangChain ReAct agents thrive on iterative tool use. You give the agent `send_sms_message`, and it decides when to fire off a text based on your chain's logic. If you need standard formatting, the agent calls `list_sms_templates` first to grab approved copy. Because this is an MCP Server, the inputs and outputs of every text message flow directly into LangSmith. You see exactly what the agent sent, how long the API took, and the raw response from Dexatel.

Automate Delivery Resolution

Delivery failures happen. Your agent can handle them automatically. When a text drops, the chain triggers `list_failed_sms_deliveries` to pull the error logs. The agent then runs `get_sms_message_details` to inspect the exact payload that bounced. Instead of waking you up at 2 AM, the ReAct loop parses the failure code, corrects the phone number format, and tries again.

Validate Contacts and Budgets

Smart agents check their constraints before acting. Before launching a broadcast, your chain executes `list_messaging_contacts` to build the target list. It follows up with a quick ping to `get_account_balance_metadata`. If the account funds are too low for the batch size, the chain halts and alerts you instead of failing halfway through the run.

Setup guide

Set up Dexatel 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 Dexatel 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({
    "dexatel-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 Dexatel transactions"
    })
    print(result["messages"][-1].content)

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Common questions about Dexatel MCP in LangChain

Install the `langchain-mcp-adapters` package. Initialize a `MultiServerMCPClient` pointing to your Vinkius endpoint, call `client.get_tools()`, and pass that array to your agent constructor.

Yes. Give your agent the failure listing tool. The ReAct loop will spot the failure, diagnose it, and fire a new message without your intervention.

It tracks everything. Every tool invocation logs the exact string passed to the API and the JSON response returned by the server.

You filter the list returned by the client. Just pass the specific tool names you want before binding them to the LLM.

Vinkius runs the server inside a V8 Isolate Sandbox. Your contact numbers pass through an ephemeral, zero-trust environment that wipes all memory the millisecond the request finishes.

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