How to Use the CM.com MCP in LangChain

Q: How do I add the CM.com MCP Server to my LangChain setup?

Install langchain-mcp-adapters via pip. Initialize the MultiServerMCPClient with your Vinkius URL, call gettools(), and pass the retrieved CM.com tools to your agent. This registers the tools directly into your LangChain environment.

Q: Can I run bulk messaging campaigns with this setup?

Yes, your agent can call sendbulksms with list data parsed from your chain's inputs. This allows for high-throughput messaging driven by agentic decisions.

Route messaging pipelines and handle user verification directly within your LangChain chains using the CM.com platform.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect CM.com MCP to LangChain

Create your Vinkius account to connect CM.com 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 CM.com with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Multi-channel dispatch with LangChain chains

The `send_sms` tool transmits text alerts, while `send_whatsapp` routes structured templates to users. LangChain links these CM.com tools sequentially. If an SMS delivery fails, the agent automatically switches to WhatsApp or triggers `send_email` in the next step of your chain. You map these CM.com transitions using LangGraph. The output of one messaging tool feeds directly into the next decision block. LangSmith traces the entire flow, showing you the exact latency of each CM.com API call and the raw payloads sent during execution.

Automated verification using this MCP Server

The `send_otp_sms` tool issues temporary verification codes, while `verify_otp` checks the user's response. Your LangChain chain manages this validation loop using CM.com tools without manual backend routing. You can also deploy `send_voice_otp` as a backup channel when text delivery fails. Agents execute these steps dynamically based on user prompts. The agent receives the validation status from the CM.com platform, letting it decide whether to unlock the next chain step or prompt the user to retry.

Balance-aware messaging pipelines

The `get_balance` tool checks your current account funds, and `list_numbers` retrieves your active sender IDs. LangChain agents query these CM.com tools before launching massive outreach campaigns. If the balance falls below a specific threshold, the agent halts the chain or alerts your team. This prevents failed delivery attempts due to insufficient funds. By routing these tool outputs directly into your agent's decision logic, you ensure your automated workflows never run dry mid-campaign.

Setup guide

Set up CM.com 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 CM.com 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({
    "cmcom-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 CM.com 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 CM.com. 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 CM.com 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 CM.com MCP in LangChain

Install `langchain-mcp-adapters` via pip. Initialize the `MultiServerMCPClient` with your Vinkius URL, call `get_tools()`, and pass the retrieved CM.com tools to your agent. This registers the tools directly into your LangChain environment.

Yes. Your LangChain agent handles this by evaluating the output of `send_otp_sms` and, if needed, calling `send_voice_otp` in the next step of the chain.

LangSmith captures every tool execution, showing the exact payloads sent to `send_sms` or `send_email`. You see real-time latency and token usage for each communication step.

Yes, your agent can call `send_bulk_sms` with list data parsed from your chain's inputs. This allows for high-throughput messaging driven by agentic decisions.

Vinkius runs this MCP Server in an isolated sandbox, meaning your API keys, SMS text content, and destination phone numbers are never stored on our platform. All transmission to CM.com occurs over encrypted connections, and the container is destroyed immediately after processing.

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