How to integrate NMKR Studio MCP with Mastra AI

This guide walks you through connecting NMKR Studio to Mastra AI using the Composio tool router. By the end, you'll have a working NMKR Studio agent that can list your nft projects, inspect nfts, check mint prices, validate metadata, and view payout wallets through natural language commands. This guide will help you understand how to give your Mastra AI agent real control over a NMKR Studio account through Composio's NMKR Studio MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

NMKR Studio logoNMKR Studio
Api Key

NMKR Studio is an NFT platform and API suite for Cardano project creation, asset management, minting, sales, and wallets. Use it to run NFT drops and Cardano asset workflows without building the whole blockchain backend yourself.

11 Tools

Introduction

This guide walks you through connecting NMKR Studio to Mastra AI using the Composio tool router. By the end, you'll have a working NMKR Studio agent that can list your nft projects, inspect nfts, check mint prices, validate metadata, and view payout wallets through natural language commands.

This guide will help you understand how to give your Mastra AI agent real control over a NMKR Studio account through Composio's NMKR Studio MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate NMKR Studio with

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 NMKR Studio tools
  • Connect Mastra's MCP client to the Composio generated MCP URL
  • Fetch NMKR Studio 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 NMKR Studio 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 NMKR Studio MCP server, and what's possible with it?

The NMKR Studio MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your NMKR Studio account. It provides structured and secure access to your projects, NFTs, sales settings, wallet information, and Cardano market data, so your agent can review projects, inspect NFTs, check sale settings, monitor balances, and retrieve exchange rates on your behalf.

  • Project and NFT tracking: Have your agent list your projects, review project details and NFT state counts, and browse NFTs by lifecycle state.
  • NFT details and metadata checks: Direct your agent to retrieve a specific NFT, inspect its stored details, and verify whether its metadata is valid.
  • Pricing and sale reviews: Let the agent check current NFT prices and active sale conditions for your projects.
  • Wallet and mint coupon monitoring: Instruct your agent to list configured payout wallets and check your current Cardano mint coupon balance.
  • Token and exchange rate lookup: Have your agent retrieve blockchain token metadata and check current ADA, BTC, USD, EUR, or JPY conversion rates available through NMKR.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step09 STEPS
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
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard 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.
  • Go to Settings and copy your API key.
  • This key lets your Mastra agent talk to Composio and reach NMKR Studio through MCP.
3

Install dependencies

bash
npm install @composio/core @mastra/core @mastra/mcp @ai-sdk/openai dotenv

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
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

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
5

Import libraries and validate environment

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,
});
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
6

Create a Tool Router session for NMKR Studio

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

  const composioMCPUrl = session.mcp.url;
  console.log("NMKR Studio MCP URL:", composioMCPUrl);
What's happening:
  • create spins up a short-lived MCP HTTP endpoint for this user
  • The toolkits array contains "nmkr_studio" for NMKR Studio access
  • session.mcp.url is the MCP URL that Mastra's MCPClient will connect to
7

Configure Mastra MCP client and fetch tools

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);
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 NMKR Studio toolkit
8

Create the Mastra agent

typescript
const agent = new Agent({
    name: "nmkr_studio-mastra-agent",
    instructions: "You are an AI agent with NMKR Studio tools via Composio.",
    model: "openai/gpt-5",
  });
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
9

Set up interactive chat interface

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: {
        nmkr_studio: 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);
});
What's happening:
  • messages keeps the full conversation history in Mastra's expected format
  • agent.generate runs the agent with conversation history and NMKR Studio 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

Complete Code

Here's the complete code to get you started with NMKR Studio and Mastra AI:

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: ["nmkr_studio"],
  });

  const composioMCPUrl = session.mcp.url;

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

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "nmkr_studio-mastra-agent",
    instructions: "You are an AI agent with NMKR Studio 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: { nmkr_studio: 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 NMKR Studio 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
TOOLS

Supported Tools

Every NMKR Studio action and event your agent gets out of the box.

Get Exchange Rates

Return NMKR's current BTC, USD, EUR, and JPY conversion rates for a supported coin; omitting coin requests the provider's ADA default.

Get Mint Coupon Balance

Return the connected account's Cardano mint-coupon balance, effective time, and documented mint-purchase address.

Get NFT

Return one NFT's details using either its NMKR NFT UID or the combination of project UID and NFT name.

Get Project

Return details and NFT state counts for an NMKR Studio project identified by its project UID.

Get Project Pricelist

Return the currently valid NFT prices configured for an NMKR Studio project, optionally including all prices exposed by NMKR.

Get Project Sale Conditions

Return the active sale conditions configured for an NMKR Studio project.

Get Token Metadata

Return metadata for a blockchain token identified by policy ID and hex-encoded token name.

List Payout Wallets

Return payout wallets already configured on the connected NMKR Studio account; this tool does not add, validate, or expose wallet secrets.

List Project NFTs

Return one page of NFTs in a project filtered by lifecycle state, with a continuation cursor for additional pages.

List Projects

Return one page of projects owned by the connected NMKR Studio account, including identifiers needed by project and NFT tools.

Validate NFT Metadata

Check whether the metadata already stored for an NFT is valid; this read-only form does not submit or update metadata.

FAQ

Frequently asked questions

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

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 NMKR Studio tools.

Yes, absolutely. You can configure which NMKR Studio 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.

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 NMKR Studio data and credentials are handled as safely as possible.

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