How do I get Instamojo API credentials?

Log in to your Instamojo dashboard, navigate to API & Plugins, and find your Client ID and Client Secret in the OAuth2 section.

Does it support Sandbox mode?

This implementation uses the production API base by default. To use sandbox, the engine URL needs to be updated.

Can I process refunds?

This version focus on listing and retrieving refund details. Actions to trigger new refunds may be added in future updates.

Instamojo MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: Instamojo
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Instamojo through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Instamojo "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Instamojo?"
    )
    print(result.data)

asyncio.run(main())

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Instamojo MCP Server

Empower your AI agents to manage your Indian payment ecosystem with Instamojo. This MCP server allows you to list and retrieve payments, manage payment requests, track refunds, view payouts, and monitor disputes directly through the Instamojo API. Ideal for automating e-commerce operations and financial monitoring in India.

Pydantic AI validates every Instamojo tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

The Instamojo MCP Server exposes 10 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Instamojo to Pydantic AI via MCP

Follow these steps to integrate the Instamojo MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 10 tools from Instamojo with type-safe schemas

Why Use Pydantic AI with the Instamojo MCP Server

Pydantic AI provides unique advantages when paired with Instamojo through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Instamojo integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Instamojo connection logic from agent behavior for testable, maintainable code

Instamojo + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Instamojo MCP Server delivers measurable value.

Type-safe data pipelines: query Instamojo with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Instamojo tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Instamojo and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Instamojo responses and write comprehensive agent tests

Instamojo MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Instamojo to Pydantic AI via MCP:

get_payment

Retrieves details for a specific payment

get_payment_request

Retrieves details for a specific payment request

get_refund

Retrieves details for a specific refund

list_disputes

Lists all active and past disputes

list_gateways

Lists configured payment gateways

list_links

Lists all generated payment links

list_payment_requests

Lists all payment requests created

list_payments

Lists all payments received

list_payouts

Lists all payouts to your bank account

list_refunds

Lists all refunds processed

Example Prompts for Instamojo in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Instamojo immediately.

"List all recent payments in Instamojo."

"Show me the status of my recent payment requests."

"Check for any active disputes in my account."

Troubleshooting Instamojo MCP Server with Pydantic AI

Common issues when connecting Instamojo to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Instamojo + Pydantic AI FAQ

Common questions about integrating Instamojo MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Instamojo MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.