How to Use the Custify MCP in LangChain

Build multi-step chains that pull Custify data directly into your LangChain workflows.

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Works with every AI agent you already use

…and any MCP-compatible client

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Connect Custify MCP to LangChain

Create your Vinkius account to connect Custify 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 Custify with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Chain Custify tools in LangChain pipelines

Feed the output of `get_customer_details` directly into your next processing block. Your agent strings together calls to track health scores without manual intervention. This MCP Server lets LangChain agents decide which data to pull based on previous chain results. It keeps your logic flowing from initial customer lookups to final task summaries.

Trace every Custify call in LangSmith

Monitor exactly how your agent interacts with the `list_customer_success_tasks` endpoint. Every request appears in your traces with full input and output metadata. Debugging becomes simple when you see the raw JSON returned by the Custify API. You catch bad tool calls before they break your downstream chain logic.

Automate account status updates with LangGraph

Use `create_customer_profile` within a stateful graph to update your system when conditions change. Your agent manages the state transitions based on live feedback from the backend. This architecture keeps your CRM records current as the agent processes new info. You define the flow, and the agent executes the Custify mutations as needed.

Setup guide

Set up Custify 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 Custify 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({
    "custify-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 Custify 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 Custify. 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 Custify 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 Custify MCP in LangChain

Install the necessary adapters and initialize the client with your endpoint URL. Pass the tools retrieved from the server into your agent constructor to enable access.

Yes, you can chain multiple tools to get specific results. For instance, use `list_customers` to find an ID, then pipe that ID into `get_customer_details`.

It does. You can use client sessions to maintain context across multiple turns of your conversation. This keeps your agent aware of previous company metrics.

Every call is fully observable. Since this is a standard-compliant server, LangSmith captures the inputs and outputs for every request made.

We enforce strict transport security for every request. The server only touches your CRM notes and customer profiles, and it never stores your data on Vinkius servers.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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