How to Use the Razorpay MCP in AutoGen

Use AutoGen agents to debate and verify your Razorpay financial operations before execution.

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Connect Razorpay MCP to AutoGen

Create your Vinkius account to connect Razorpay to AutoGen 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 AutoGen

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Debate Razorpay actions in AutoGen

Assign one agent to audit and another to execute. They discuss the validity of a `create_order` request before finalizing it. This prevents accidental duplicate transactions. The agents challenge each other based on the data retrieved from `get_order`.

Automate reconciliation with AutoGen

Let a finance agent compare bank transfers against your internal ledger. It uses `list_transfers` to pull data and flags discrepancies. Conflict resolution is automatic. If the numbers don't match, the agents report the issue instead of pushing bad data.

Negotiate settlement cycles via agents

A performance agent monitors `list_settlements` to track cash flow. It coordinates with a planning agent to optimize your payment schedules. They reach a consensus on when to trigger new orders. This removes the need for manual oversight of your financial timing.

Setup guide

Set up Razorpay MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Razorpay tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Razorpay_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Razorpay data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Razorpay_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Razorpay data")
    print(result.messages[-1].content)

Get your connection token →

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