How to Use the Razorpay MCP in LangChain

Q: How do I track Razorpay tool usage in LangChain?

LangSmith provides built-in observability. Every call to listsettlements or other tools is captured as a distinct step in your trace.

Chain Razorpay payment data into complex LangChain reasoning pipelines to automate your financial workflows.

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Connect Razorpay MCP to LangChain

Create your Vinkius account to connect Razorpay 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 Razorpay with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Sequence payment actions in LangChain

Build multi-step chains that trigger `create_order` based on your business logic. The agent holds the state and handles the sequence of events without manual intervention. Your agent passes data between tools. It uses the output from `list_payments` to determine if a refund is necessary, then calls `list_refunds` to confirm.

Trace Razorpay calls with LangSmith

Every tool execution is logged for full visibility. You see exactly how the agent interacts with your financial data through standard tracing. Debugging is straightforward when you monitor inputs to `get_order`. You identify latency issues or incorrect parameters before they reach the payment gateway.

Aggregate data across MCP servers

Connect this MCP server alongside your database or CRM tools. Your LangChain agent pulls customer details from your records and creates an order in one flow. Use `list_customers` to verify identity before calling `create_customer`. The agent manages the entire process within your defined logic.

Setup guide

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Razorpay. 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.

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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 Razorpay MCP in LangChain

Install the MCP adapters and point your client to the Vinkius endpoint. You then pass the tool list directly into your agent constructor to enable access.

Yes. You define retry logic or fallback chains in your pipeline. If `get_payment` returns a failure, the agent reacts based on the instructions you provided.

The server uses ephemeral sessions managed by Vinkius. Only the tools you explicitly permit can access your sensitive financial records.

LangSmith provides built-in observability. Every call to `list_settlements` or other tools is captured as a distinct step in your trace.

Data is processed in memory during the agent's turn. It does not persist unless you explicitly store it in your own connected vector database.

Use it with your favorite AI tools

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

OpenAI Agents SDK sdk-python