# How to integrate Niftyimages MCP with Mastra AI

```json
{
  "title": "How to integrate Niftyimages MCP with Mastra AI",
  "toolkit": "Niftyimages",
  "toolkit_slug": "niftyimages",
  "framework": "Mastra AI",
  "framework_slug": "mastra-ai",
  "url": "https://composio.dev/toolkits/niftyimages/framework/mastra-ai",
  "markdown_url": "https://composio.dev/toolkits/niftyimages/framework/mastra-ai.md",
  "updated_at": "2026-03-29T06:43:24.432Z"
}
```

## Introduction

This guide walks you through connecting Niftyimages to Mastra AI using the Composio tool router. By the end, you'll have a working Niftyimages agent that can generate a countdown image for a holiday sale, create a personalized image for each recipient, update a template with new product details through natural language commands.
This guide will help you understand how to give your Mastra AI agent real control over a Niftyimages account through Composio's Niftyimages MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Niftyimages with

- [OpenAI Agents SDK](https://composio.dev/toolkits/niftyimages/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/niftyimages/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/niftyimages/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/niftyimages/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/niftyimages/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/niftyimages/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/niftyimages/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/niftyimages/framework/cli)
- [Google ADK](https://composio.dev/toolkits/niftyimages/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/niftyimages/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/niftyimages/framework/ai-sdk)
- [LlamaIndex](https://composio.dev/toolkits/niftyimages/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/niftyimages/framework/crew-ai)

## TL;DR

Here's what you'll learn:
- Set up your environment so Mastra, OpenAI, and Composio work together
- Create a Tool Router session in Composio that exposes Niftyimages tools
- Connect Mastra's MCP client to the Composio generated MCP URL
- Fetch Niftyimages tool definitions and attach them as a toolset
- Build a Mastra agent that can reason, call tools, and return structured results
- Run an interactive CLI where you can chat with your Niftyimages agent

## What is Mastra AI?

Mastra AI is a TypeScript framework for building AI agents with tool support. It provides a clean API for creating agents that can use external services through MCP.
Key features include:
- MCP Client: Built-in support for Model Context Protocol servers
- Toolsets: Organize tools into logical groups
- Step Callbacks: Monitor and debug agent execution
- OpenAI Integration: Works with OpenAI models via @ai-sdk/openai

## What is the Niftyimages MCP server, and what's possible with it?

The Niftyimages MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Niftyimages account. It provides structured and secure access so your agent can perform Niftyimages operations on your behalf.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `NIFTYIMAGES_GET_IMAGES_STATS` | Get Images Stats | Tool to get aggregated stats for all images. Use when you need to retrieve statistical data and performance metrics for all images in the account. |
| `NIFTYIMAGES_GET_WIDGET_USER_IMAGES` | Get Widget User Images | Tool to list widget images for a specific user. Use when you need to retrieve all images associated with a particular user and widget combination. |
| `NIFTYIMAGES_GET_WIDGET_USER_STATS` | Get Widget User Stats | Tool to get aggregated stats for a specific user on a widget. Use when you need to retrieve performance metrics for a particular user's interaction with a widget. |
| `NIFTYIMAGES_LIST_IMAGES` | List Images | Tool to page through images in your NiftyImages account. Use when you need to retrieve a list of all available images. |
| `NIFTYIMAGES_LIST_MAPS` | List Maps | Tool to retrieve all maps in your NiftyImages account. Use when you need to view all available maps for geo-targeting or location-based email content. |
| `NIFTYIMAGES_LIST_WIDGET_IMAGES` | List Widget Images | Tool to list widget images for a time frame. Use when you need to retrieve images generated by a specific widget within an optional date range. |
| `NIFTYIMAGES_LIST_WIDGETS` | List Widgets | Tool to list all widgets in your NiftyImages account. Use when you need to retrieve all available widgets. |
| `NIFTYIMAGES_LIST_WIDGET_STATS` | List widget stats | Tool to retrieve widget statistics for a specified time frame from NiftyImages. Use when you need to view performance metrics such as impressions and clicks for your widgets. |
| `NIFTYIMAGES_LIST_WIDGET_USERS` | List Widget Users | Tool to list widget users for a specified time frame from NiftyImages. Use when you need to retrieve users who interacted with a specific widget during a date range. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Niftyimages MCP server is an implementation of the Model Context Protocol that connects your AI agent to Niftyimages. It provides structured and secure access so your agent can perform Niftyimages operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. Prerequisites

Before starting, make sure you have:
- Node.js 18 or higher
- A Composio account with an active API key
- An OpenAI API key
- Basic familiarity with TypeScript

### 1. Getting API Keys for OpenAI and Composio

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) and create an API key.
- You need credits or a connected billing setup to use the models.
- Store the key somewhere safe.
Composio API Key
- Log in to the [Composio dashboard](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Go to Settings and copy your API key.
- This key lets your Mastra agent talk to Composio and reach Niftyimages through MCP.

### 2. Install dependencies

Install the required packages.
What's happening:
- @composio/core is the Composio SDK for creating MCP sessions
- @mastra/core provides the Agent class
- @mastra/mcp is Mastra's MCP client
- @ai-sdk/openai is the model wrapper for OpenAI
- dotenv loads environment variables from .env
```bash
npm install @composio/core @mastra/core @mastra/mcp @ai-sdk/openai dotenv
```

### 3. Set up environment variables

Create a .env file in your project root.
What's happening:
- COMPOSIO_API_KEY authenticates your requests to Composio
- COMPOSIO_USER_ID tells Composio which user this session belongs to
- OPENAI_API_KEY lets the Mastra agent call OpenAI models
```bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here
```

### 4. Import libraries and validate environment

What's happening:
- dotenv/config auto loads your .env so process.env.* is available
- openai gives you a Mastra compatible model wrapper
- Agent is the Mastra agent that will call tools and produce answers
- MCPClient connects Mastra to your Composio MCP server
- Composio is used to create a Tool Router session
```typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({
  apiKey: composioAPIKey as string,
});
```

### 5. Create a Tool Router session for Niftyimages

What's happening:
- create spins up a short-lived MCP HTTP endpoint for this user
- The toolkits array contains "niftyimages" for Niftyimages access
- session.mcp.url is the MCP URL that Mastra's MCPClient will connect to
```typescript
async function main() {
  const session = await composio.create(
    composioUserID as string,
    {
      toolkits: ["niftyimages"],
    },
  );

  const composioMCPUrl = session.mcp.url;
  console.log("Niftyimages MCP URL:", composioMCPUrl);
```

### 6. Configure Mastra MCP client and fetch tools

What's happening:
- MCPClient takes an id for this client and a list of MCP servers
- The headers property includes the x-api-key for authentication
- getTools fetches the tool definitions exposed by the Niftyimages toolkit
```typescript
const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      nasdaq: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

console.log("Fetching MCP tools from Composio...");
const composioTools = await mcpClient.getTools();
console.log("Number of tools:", Object.keys(composioTools).length);
```

### 7. Create the Mastra agent

What's happening:
- Agent is the core Mastra agent
- name is just an identifier for logging and debugging
- instructions guide the agent to use tools instead of only answering in natural language
- model uses openai("gpt-5") to configure the underlying LLM
```typescript
const agent = new Agent({
    name: "niftyimages-mastra-agent",
    instructions: "You are an AI agent with Niftyimages tools via Composio.",
    model: "openai/gpt-5",
  });
```

### 8. Set up interactive chat interface

What's happening:
- messages keeps the full conversation history in Mastra's expected format
- agent.generate runs the agent with conversation history and Niftyimages toolsets
- maxSteps limits how many tool calls the agent can take in a single run
- onStepFinish is a hook that prints intermediate steps for debugging
```typescript
let messages: AiMessageType[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end.\n");

const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: "> ",
});

rl.prompt();

rl.on("line", async (userInput: string) => {
  const trimmedInput = userInput.trim();

  if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) {
    console.log("\nGoodbye!");
    rl.close();
    process.exit(0);
  }

  if (!trimmedInput) {
    rl.prompt();
    return;
  }

  messages.push({
    id: crypto.randomUUID(),
    role: "user",
    content: trimmedInput,
  });

  console.log("\nAgent is thinking...\n");

  try {
    const response = await agent.generate(messages, {
      toolsets: {
        niftyimages: composioTools,
      },
      maxSteps: 8,
    });

    const { text } = response;

    if (text && text.trim().length > 0) {
      console.log(`Agent: ${text}\n`);
        messages.push({
          id: crypto.randomUUID(),
          role: "assistant",
          content: text,
        });
      }
    } catch (error) {
      console.error("\nError:", error);
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    console.log("\nSession ended.");
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main().catch((err) => {
  console.error("Fatal error:", err);
  process.exit(1);
});
```

## Complete Code

```typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({ apiKey: composioAPIKey as string });

async function main() {
  const session = await composio.create(composioUserID as string, {
    toolkits: ["niftyimages"],
  });

  const composioMCPUrl = session.mcp.url;

  const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      niftyimages: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "niftyimages-mastra-agent",
    instructions: "You are an AI agent with Niftyimages tools via Composio.",
    model: "openai/gpt-5",
  });

  let messages: AiMessageType[] = [];

  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: "> ",
  });

  rl.prompt();

  rl.on("line", async (input: string) => {
    const trimmed = input.trim();
    if (["exit", "quit"].includes(trimmed.toLowerCase())) {
      rl.close();
      return;
    }

    messages.push({ id: crypto.randomUUID(), role: "user", content: trimmed });

    const { text } = await agent.generate(messages, {
      toolsets: { niftyimages: composioTools },
      maxSteps: 8,
    });

    if (text) {
      console.log(`Agent: ${text}\n`);
      messages.push({ id: crypto.randomUUID(), role: "assistant", content: text });
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main();
```

## Conclusion

You've built a Mastra AI agent that can interact with Niftyimages through Composio's Tool Router.
You can extend this further by:
- Adding other toolkits like Gmail, Slack, or GitHub
- Building a web-based chat interface around this agent
- Using multiple MCP endpoints to enable cross-app workflows

## How to build Niftyimages MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/niftyimages/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/niftyimages/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/niftyimages/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/niftyimages/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/niftyimages/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/niftyimages/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/niftyimages/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/niftyimages/framework/cli)
- [Google ADK](https://composio.dev/toolkits/niftyimages/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/niftyimages/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/niftyimages/framework/ai-sdk)
- [LlamaIndex](https://composio.dev/toolkits/niftyimages/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/niftyimages/framework/crew-ai)

## Related Toolkits

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- [Benchmark email](https://composio.dev/toolkits/benchmark_email) - Benchmark Email is a platform for creating, sending, and tracking email campaigns. It's built to help you engage audiences and analyze results—all in one place.
- [Bigmailer](https://composio.dev/toolkits/bigmailer) - BigMailer is an email marketing platform for managing multiple brands with white-labeling and automation. It helps teams streamline campaigns and simplify integration with Amazon SES.
- [Brandfetch](https://composio.dev/toolkits/brandfetch) - Brandfetch is an API that delivers company logos, colors, and visual branding assets. It helps marketers and developers keep brand visuals consistent everywhere.
- [Brevo](https://composio.dev/toolkits/brevo) - Brevo is an all-in-one email and SMS marketing platform for transactional messaging, automation, and CRM. It helps businesses engage customers and streamline communications through powerful campaign tools.
- [Campayn](https://composio.dev/toolkits/campayn) - Campayn is an email marketing platform for creating, sending, and managing campaigns. It helps businesses engage contacts and grow audiences with easy-to-use tools.
- [Cardly](https://composio.dev/toolkits/cardly) - Cardly is a platform for creating and sending personalized direct mail to customers. It helps businesses break through the digital clutter by getting real engagement via physical mailboxes.
- [ClickSend](https://composio.dev/toolkits/clicksend) - ClickSend is a cloud-based SMS and email marketing platform for businesses. It streamlines communication by enabling quick message delivery and contact management.
- [Crustdata](https://composio.dev/toolkits/crustdata) - CrustData is an AI-powered data intelligence platform for real-time company and people data. It helps B2B sales teams, AI SDRs, and investors react to live business signals.
- [Curated](https://composio.dev/toolkits/curated) - Curated is a platform for collecting, curating, and publishing newsletters. It streamlines content aggregation and distribution for creators and teams.
- [Customerio](https://composio.dev/toolkits/customerio) - Customer.io is a customer engagement platform for targeted messaging across email, SMS, and push. Easily automate, segment, and track communications with your audience.
- [Cutt ly](https://composio.dev/toolkits/cutt_ly) - Cutt.ly is a URL shortening service for managing and analyzing links. Streamline your workflows with quick, trackable, and branded short URLs.
- [Demio](https://composio.dev/toolkits/demio) - Demio is webinar software built for marketers, offering both live and automated sessions with interactive features. It helps teams engage audiences and optimize lead generation through detailed analytics.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Niftyimages MCP?

With a standalone Niftyimages MCP server, the agents and LLMs can only access a fixed set of Niftyimages tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Niftyimages and many other apps based on the task at hand, all through a single MCP endpoint.

### Can I use Tool Router MCP with Mastra AI?

Yes, you can. Mastra AI fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Niftyimages tools.

### Can I manage the permissions and scopes for Niftyimages while using Tool Router?

Yes, absolutely. You can configure which Niftyimages scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

### How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Niftyimages data and credentials are handled as safely as possible.

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)
