How to Use the CallFire MCP in LangChain

Q: How do I pass CallFire tools to a LangChain agent?

Install langchain-mcp-adapters and connect to the Vinkius endpoint. Pass the retrieved CallFire tools directly to createagent to start running campaigns.

Q: Does LangChain trace CallFire API latency?

Yes, every execution of tools like listcalls shows up in your LangSmith dashboard. You get full visibility into the exact execution time and payload size.

Q: How does LangChain handle CallFire webhook setup?

Your agent uses getwebhook and listwebhooks to inspect active listeners during chain execution. Configure your LangChain logic to register new endpoints based on real-time campaign status.

Run CallFire voice campaigns and send bulk texts directly inside your LangChain reasoning loops.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect CallFire MCP to LangChain

Create your Vinkius account to connect CallFire 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 CallFire with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Chain CallFire SMS logs with LangChain agent memory

This MCP Server lets your LangChain agent pull live SMS conversations via `get_text` and `list_texts` to decide what to reply next. Instead of writing hardcoded API calls, you feed these tools to a ReAct agent that inspects text history on the fly.

Trace broadcast campaign stats in LangSmith

Monitor every single `get_campaign` and `list_campaigns` call your LangChain pipeline executes through these MCP tools. Catching malformed payload structures before they mess up your active voice campaigns keeps your pipelines running smoothly.

Multi-step voice campaign execution

Build complex LangChain workflows that query contacts using `list_contacts` and immediately trigger voice broadcasts. Use `get_call` and `list_calls` to evaluate call outcomes dynamically inside your chain.

Setup guide

Set up CallFire 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 CallFire 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({
    "callfire-alternative-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 CallFire 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 CallFire. 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 CallFire 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 CallFire MCP in LangChain

Install `langchain-mcp-adapters` and connect to the Vinkius endpoint. Pass the retrieved CallFire tools directly to `create_agent` to start running campaigns.

Yes, every execution of tools like `list_calls` shows up in your LangSmith dashboard. You get full visibility into the exact execution time and payload size.

Your agent uses `get_webhook` and `list_webhooks` to inspect active listeners during chain execution. Configure your LangChain logic to register new endpoints based on real-time campaign status.

You combine this server with database or CRM servers in a single MultiServerMCPClient. Your LangChain agent queries contacts from your CRM and feeds them directly to CallFire tools.

Your phone numbers, SMS content, and call logs stay inside the ephemeral V8 Isolate Sandbox. Vinkius never stores these payloads, passing them securely between your LangChain environment and the CallFire API.

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