How to Use AI Tools in Crypto App Development

Last updated: August 14, 202511 min read

Using AI tools in crypto app development

AI is changing how developers build in Web3, not by replacing people, but by helping developers accelerate through the initial development phase and focus on higher-level problem-solving.

Instead of wasting hours centering a div or debugging an obscure Ethers.js error, devs are using AI tools to spin up UIs, write safe contracts, scaffold backends, and troubleshoot weird wallet issues.

In this guide, we’ll walk through how real developers are putting AI to work across the stack. We’ll look at tools like Cursor, ChatGPT, Claude, Replit, Alchemy infra for AI Agents and more, with working code, common errors, and real-world setup examples.

Understanding Crypto App Development

Crypto app development isn’t just deploying a smart contract. It means building an end-to-end experience that runs onchain often across multiple layers:

A smart contract (Solidity, Rust, etc.)
A frontend (React, Next.js, etc.)
Wallet integration (e.g., Alchemy Smart Wallets)
Backend services or APIs
Blockchain data indexing/querying

And sometimes building a crypto app goes beyond writing smart contracts. You might need a custom environment to handle transactions, which used to involve deep blockchain know-how and heavy setup. Tools like Alchemy Rollups now make this much easier.

With a few commands, you can launch a "rollup" which is a faster, low-cost layer that works alongside the main blockchain. It’s great for apps that need speed, scalability, or more control. And you don’t need to be a blockchain expert to use it.

But more options mean more complexity and from smart contracts and frontends to wallets and rollups, the complexity can stack up quickly. And through it all, your app still needs to be secure, composable, and gas-efficient.

And AI helps developers stay in flow. Instead of switching between Stack Overflow tabs and outdated docs, you can query AI with the actual context of your project and get targeted help.

The best way to see what AI can do for your crypto app is to watch it in action. This article is packed with tools that crypto app developers are already using to move faster, fix smarter, and launch with confidence.

We’ll walk through AI tools like ChatGPT, Claude, Cursor, and others, each bringing something different to the table. From generating smart contract tests to debugging tricky wallet issues, these tools are reshaping the way crypto apps get built. Whether you're experimenting on weekends or scaling a live app, this article will show you how to weave AI tools into your workflow and why it's quickly becoming a must-have for every developer.

AI Tools to Integrate Into Your Crypto App Development Workflow

Cursor AI: the IDE That Understands Your Codebase

Cursor is a specialized AI-first IDE built on top of VS Code. Unlike traditional plugins, Cursor's AI integrates at the IDE level with full access to file context, memory, and navigation.

For crypto app developers, this means you can:

Reference specific contracts or components in prompts using @ mentions.
Pull in your own documentation (e.g., Alchemy's Smart Wallets SDK) and query it alongside your code.
Scaffold full-stack apps with preconfigured dependencies.
Debug Solidity functions without leaving your editor.
Generate automated test suites tailored to your contracts.

Key Features of Cursor:

Contextual Awareness with @ Mentions

Tag files and folders with @MyContract.sol or @/components in prompts.

Example:

“@ERC20.sol Why is my transferFrom() failing when allowance is set?”

Documentation Context Integration

Upload docs (e.g. Alchemy SDK). Index them in-memory and reference using prompts like:

“@alchemy docs what does getAssetTransfers() return?”

MVP Generation

Cursor will create the file structure, dependencies, and base UI in seconds.

Example:

“Build a React dApp with Alchemy Smart Wallet and fetch NFT balances.”

Smart Contract Debugging

Cursor will explain the issue based on access control logic.

Example:

“@MyContract.sol Why is the mint function reverting for users without role 0x01”

Automated Testing

Example:

"Write Foundry tests for ERC-721 minting with edge cases (supply cap, invalid caller)."

Example: Build a Full Stack dApp with Alchemy Smart Wallets using AI

Prompt:

Create a full stack app with Alchemy Smart Wallets using @Alchemy docs and write boilerplate smart contract for NFT minting functions.

This kind of prompt works perfectly in AI-powered IDEs like Cursor. The AI will:

Reference the Alchemy docs for Smart Wallet integration details and more.
Pull in best practices for an NFT minting smart contract.
Generate a Next.js frontend with Alchemy Smart Wallets (or another stack of your choice, this is just one example setup)
Scaffold a starter ERC‑721 contract with supply caps and per-wallet limits.
Create a Hardhat deployment script.
Set up a minimal backend API using the Alchemy SDK for fetching NFT data.

With one request, you can have a fully functional starter dApp ready to deploy.

ChatGPT: Flexible AI Support Across the Stack

ChatGPT is a powerful tool for working across the full web3 development stack. It’s especially useful for:

Troubleshooting SDKs and APIs
Generating code snippets for both frontend and backend
Answering smart contract questions and helping debug logic

Example: Debugging a Smart Contract Error With an AI Prompt

Prompt:

"Why does my transfer function fail when msg.sender is not owner?"

ChatGPT can quickly spot issues like missing access control modifiers (onlyOwner) or flaws in how permissions are being checked.

Example: Using AI to Write Ethers.js to Fetch Token Balances

Prompt:

"Write a function in Ethers.js that fetches the balance of a given ERC20 token."

Response:

javascriptCopied
import { Network, Alchemy } from 'alchemy-sdk';

// Optional Config object, but defaults to demo api-key and eth-mainnet.
const settings = {
  apiKey: 'demo', // Replace with your Alchemy API Key.
  network: Network.ETH_MAINNET, // Replace with your network.
};

const alchemy = new Alchemy(settings);

// Fetch ERC-20 token balance for a specific wallet and token
alchemy.core
  .getTokenBalances('0x3f5CE5FBFe3E9af3971dD833D26bA9b5C936f0bE', ['0xA0b86991c6218b36c1d19D4a2e9Eb0cE3606eB48']) // Example: USDC
  .then(console.log);

Explanation:

Alchemy SDK simplifies access to Ethereum and includes enhanced APIs out of the box.
alchemy.core.getTokenBalances fetches token balances for a given wallet address.
You can pass in one or multiple token addresses to query specific ERC-20 balances.

You can also use ChatGPT to generate deployment scripts, config files for Hardhat, Foundry, or Brownie, and custom frontend hooks tailored to your project.

Claude: Deep Context Reasoning AI for Contract Engineering

Claude’s strength lies in understanding and operating on large codebases with high context windows. It’s ideal for:

Smart contract audits.
Protocol architecture feedback.
Refactoring complex systems.

Example: Audit a Vault Contract using an AI Prompt

Prompt:

"Identify risks in this Solidity vault contract with withdrawal and deposit logic."

Claude might detect:

Reentrancy vulnerabilities.
Missed balance updates.
Non-compliant fallback logic.

⚠️ AI tools like Claude can spot common issues, but don’t rely on them alone for security audits. Always follow up with manual reviews and expert eyes, especially for contracts holding real value.

Refactoring Example

Prompt:

"Split this monolithic contract into upgradable proxy pattern with separate logic and storage contracts."

Claude will return multiple files, clear separation of concerns, and security considerations.

Lovable: AI Tool for Prompt-to-Frontend with Design System Integration

Lovable enables frontend development from:

Raw prompts
Figma files
Component-level requests

Example Prompt for AI:

"Generate a dashboard with a token balance card, price chart (via CoinGecko), and Connect Wallet button."

Generated stack:

React with Tailwind CSS
Card.tsx, Wallet.tsx, Chart.tsx
API calls for token price

Supabase support allows you to go from frontend-only to full-stack.

Example Code Output (Wallet.tsx) from AI:

typescriptCopied
import { ConnectButton } from '@rainbow-me/rainbowkit';

export default function Wallet() {
  return (
    <div className="p-4">
      <ConnectButton />
    </div>
  );
}

Lovable is ideal for solo builders who want fast iteration with design consistency.

Bolt: One-Prompt Full-Stack dApp Scaffolding Using AI

Bolt.new allows you to create a working crypto app with one descriptive prompt. It generates:

Smart contract
Frontend (React, Next.js)
SDK/API integrations

Example Prompt for AI:

"Build a Base L2 dApp where users can mint a limited-edition NFT, view their holdings, and receive confirmation via email."

Output Includes:

MintNFT.sol with capped supply logic.
Frontend with pages/index.tsx, Alchemy integration.
Optional Supabase or Postmark email webhook integration.

Bolt.new also includes commands to run and test the entire system locally or deploy to testnet.

Replit: Real-Time Cloud Dev and AI Automation for Web3

Replit is a cloud-based, always-on development environment that supports a wide range of languages including JavaScript, Python, and Solidity. For crypto developers, it stands out for its speed, simplicity, and built-in AI features.

Here’s what makes it especially useful for Web3:

Instantly prototype smart contracts or APIs, no setup required.
Use Ghostwriter, Replit’s AI assistant, to generate or refactor code on the fly.
Collaborate with your team in real time, with live code sharing.
Deploy dApp backends fast using Replit’s serverless hosting.

Getting Started with Solidity

Replit comes with Solidity environments ready to go. You can:

Write, compile, and test contracts using templates built on Hardhat or Foundry.
Use Ghostwriter AI to scaffold entire contracts from just a simple prompt.

Prompt:

"Create a Solidity contract that locks ETH for 7 days and allows withdrawal only after."

Ghostwriter AI’s Output:

solidityCopied
pragma solidity ^0.8.20;

contract TimeLock {
    // Stores ETH balances for each address
    mapping(address => uint256) public balances;

    // Stores unlock timestamps per address
    mapping(address => uint256) public unlockTime;

    // Accepts ETH and locks it for 7 days
    function lockFunds() external payable {
        require(msg.value > 0, "Send ETH");
        balances[msg.sender] += msg.value;
        unlockTime[msg.sender] = block.timestamp + 7 days;
    }

    // Allows withdrawal only after unlock time
    function withdraw() external {
        require(block.timestamp >= unlockTime[msg.sender], "Still locked");
        uint256 amount = balances[msg.sender];
        balances[msg.sender] = 0;
        payable(msg.sender).transfer(amount);
    }
}

Explanation:

lockFunds: accepts ETH deposits and sets a 7-day unlock timer.
withdraw: lets users claim their ETH only after the timer has passed.

Use Replit AI to Write Code for Monitoring and Webhooks with Node.js

You can use Replit AI to write backends that listen for on-chain events:

javascriptCopied
// Import the Alchemy SDK and Express.js server
const { Alchemy, Network } = require("alchemy-sdk");
const express = require("express");
const app = express();

// Alchemy API setup: add your API key and desired network
const config = {
  apiKey: process.env.ALCHEMY_KEY,
  network: Network.ETH_SEPOLIA, // Can be ETH_MAINNET, MATIC_MAINNET, etc.
};
const alchemy = new Alchemy(config);

// Use Alchemy WebSockets to listen for Transfer events in real-time
alchemy.ws.on("Transfer", (log) => {
  if (Number(log.value) > 1e18) {
    console.log("Whale transfer detected:", log);
  }
});

// Spin up a basic Express server for any additional endpoints
app.listen(3000, () => console.log("Listening on port 3000"));

Explanation:

Connects to Alchemy’s WebSocket endpoint on Sepolia testnet.
Listens for ERC-20 Transfer events and logs large transfers.
Starts an Express server for any additional API or webhook logic.

Deploy Backend Services

Replit supports persistent deployments:

Host webhook handlers or analytics endpoints.
Store user data using Replit DB or PostgreSQL plugin.
Automate scheduled tasks for monitoring chain state.

With proper .env setup and lightweight Node.js code, devs can spin up observability dashboards or custom Discord bots directly from Replit.

Replit makes it easy to iterate across frontend/backend/contract layers, especially for developers who want fast feedback cycles, team collaboration, and built-in AI help.

AI Tooling for Error Handling in Smart Contracts and Backends

AI tools can assist with robust error handling. When generating contracts or backend scripts, consider using AI tools to embedding logs and fallback checks for observability.

You can prompt AI tools to:

Add revert conditions to prevent invalid transactions.
Suggest logging strategies for backend scripts.
Generate test cases for specific error scenarios.

Example prompts:

"Suggest safe error handling patterns for an ERC-721 mint function with a supply cap."

"Add descriptive logging to this mint transaction handler so failures are easy to debug."

Then, AI can output something like:

Smart Contract Example with Revert Logging

solidityCopied
function mint(uint256 amount) external {
    // Guard clause for zero amount
    if (amount == 0) {
        revert("Mint amount must be greater than zero");
    }

    // Prevent exceeding supply cap
    require(totalSupply() + amount <= MAX_SUPPLY, "Exceeds supply");

    // Proceed to mint
    _mint(msg.sender, amount);
}

Backend Logging Example

javascriptCopied
try {
  // Attempt to execute mint transaction
  const tx = await contract.methods.mint().send({ from: user });
  console.log("Success:", tx);
} catch (err) {
  // Log error with descriptive context
  console.error("Mint failed:", err.message);
}

Chaining AI Tools Together in a Workflow

Smart devs combine AI tools to cover the full stack. Here's how:

Use Claude to generate the base smart contract
Prompt: "Write an upgradable ERC-721A contract with per-wallet minting limits and whitelist support."
Import into Cursor IDE
Paste or load the Claude-generated contract.
Prompt Cursor: "Generate tests for this contract using Foundry."
Generate frontend in Bolt or Lovable
Prompt Bolt: "Build a frontend to connect wallet, whitelist mint, and display user NFTs."
Debug edge cases using ChatGPT
Prompt: "Why does RainbowKit fail to detect MetaMask on Safari mobile?"

Troubleshooting Scenarios Using AI tools

Alchemy Smart Wallet Not Displaying or Initializing Properly

This example shows how AI can help with a very specific but high-friction issue that often blocks Web3 app launches: wallet integrations.

In practice, AI tools can speed up diagnosing these wallet-specific errors by reading your actual code and project setup, cross-referencing SDK docs, and suggesting exact code changes.

Common issues AI can help identify:

AlchemyAccountsProvider not wrapping your app.
Missing or incorrect createConfig() setup.
QueryClientProvider not provided.
API key or chain misconfiguration.
Server-side rendering not handled correctly.

AI-powered fix suggestion:

typescriptCopied
import { AlchemyAccountsProvider } from "@account-kit/react";
import { config, queryClient } from "./walletConfig";//contains createConfig and QueryClient setup shown earlier
import { QueryClientProvider } from "@tanstack/react-query";

function App({ Component, pageProps }) {
  return (
    <QueryClientProvider client={queryClient}>
      <AlchemyAccountsProvider config={config}>
        <Component {...pageProps} />
      </AlchemyAccountsProvider>
    </QueryClientProvider>
  );
}

Checklist:

createConfig() is called with valid apiKey and chain.
Wrapped in both AlchemyAccountsProvider and QueryClientProvider.
No mismatches between SSR flags and framework setup (e.g., Next.js).
Wallet UI (<AccountButton />) is used inside a component rendered after hydration.

Optional AI Prompt:

"Help me debug why Alchemy Smart Wallet isn't showing in my React app (using @account-kit/react). Here's my config..."

This prompt will give you updated code checks and integration help from AI agents familiar with Alchemy SDK patterns.

Building Onchain AI Workflows with Alchemy Infra and MCP

Developers can use Alchemy’s core infrastructure, including smart wallets, Data APIs, and the Modern Context Protocol (MCP), to power AI-driven onchain workflows. Together, these capabilities enable the creation of ai agents that securely manage wallets, execute transactions, and move assets across multiple chains with consistent reliability and safety.

Learn more at alchemy.com/ai-agents.

What These Tools Enable for Devs

Here’s how these tools help devs in onchain AI development and support each step of a developer’s workflow:

Secure Wallet Management: Agents use smart wallets with detailed permission controls, optional human-in-the-loop approvals, and built-in spending limits, giving you strong guardrails for automation.
AI-Tuned Blockchain Data: Alchemy’s Modern Context Protocol (MCP) gives agents access to real-time, cross-chain data including portfolio insights, transfer history, token prices, and more. No manual indexing needed.
Deploy Across 50+ Chains: Developers can build agent once, and run it anywhere, while Alchemy’s APIs ensure consistent performance.

What’s Model Context Protocol (MCP)?

In this section we will explore MCPs, and how we can use AI to query on-chain data.

MCP (Modern Context Protocol) is the structured interface that lets AI agents pull in blockchain data without having to build custom indexing logic. It gives your agent high-context visibility into on-chain activity from the start.

With MCP, your AI can:

Pull real-time, multi-chain blockchain data on demand.
Access information like token prices, transactions, NFTs, and wallet activity.
Operate without custom backend infrastructure for indexing.

Here’s an example MCP server config you can integrate into tools like Cursor or Claude to give AI direct access to on-chain data:

jsonCopied
{
  "mcpServers": {
    "alchemy": {
      "command": "npx",
      "args": ["-y", "@alchemy/mcp-server"],
      "env": {
        "ALCHEMY_API_KEY": "YOUR_API_KEY"
      }
    }
  }
}

Supported MCP Methods (AI-Callable)

fetchTokenPriceBySymbol
fetchTokenPriceByAddress
fetchTokenPriceHistoryBySymbol
fetchTokensOwnedByMultichainAddresses
fetchMultichainWalletAddressTransactionHistory
fetchTransfers
fetchNftsOwnedByMultichainAddresses
fetchNftContractDataByMultichainAddress

Getting Onchain Data Using MCP-Connected AI

Here, we are making a query in natural language asking an MCP-connected AI to find all NFTs a specific wallet owns across Base and Ethereum, along with each NFT’s floor price. The AI converts this into a structured MCP method call.

Prompt:

"Get the NFTs owned by wallet 0x123... on Base and Ethereum. Show floor prices."

The AI calls:

jsonCopied
{
  "method": "fetchNftsOwnedByMultichainAddresses",
  "params": {
    "addresses": ["0x123..."],
    "chains": ["base-mainnet", "eth-mainnet"]
  }
}

In the output, we will get the requested data from AI in a structured manner.

Using MCP Inspector for Debugging

Alchemy’s MCP Inspector helps devs debug their MCP server by providing a visual frontend interface to test their methods on the MCP.

To start the MCP Inspector UI run following commands in the terminal.

To install all the dependencies:

bash

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pnpm install

To start the frontend:

bash

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pnpm inspector

This opens a local dashboard where you can:

Test methods
View responses
Validate inputs
Debug errors

With this, you can test MCP features with a visual frontend.

Checkout the Github for Alchemy’s MCP, and you can also contribute to MCP’s Open source codebase.

Real-World Use Case: Onchain AI Layers

Onchain AI is not just about building with AI tools or deploying autonomous agents, some are even creating entire AI-oriented blockchain layers, purpose-built for AI workloads, and open for anyone to build on.

Virtuals Protocol

Virtuals Protocol leveraged Alchemy's smart wallets and Agent Commerce Protocol (ACP) to process over $8B+ in onchain value across 17,000 autonomous agents.

Capabilities

Savings agents: Automated yield strategies (e.g., Moonwell yield bots).
Market analytics & trading bots: Real-time data analysis and execution.
Creator economy agents: Monetization tools for digital creators.

Outcome: Fully autonomous onchain agents that coordinate and transfer value without human intervention.

Gensyn

Gensyn is building a decentralized AI compute network, a blockchain layer that coordinates and verifies AI training and inference across distributed compute providers.

Capabilities

AI compute marketplace: Match compute buyers and sellers.
Onchain verification: Ensure integrity of training and inference jobs.
Scalable coordination: Handle global participation in AI workloads.

Outcome: Trust-minimized AI compute accessible from anywhere.

Gaia Network

Gaia is a blockchain ecosystem focused on hosting and running AI-native applications via a decentralized node network, rather than inside smart contracts. Its data marketplace is in development, aiming to expand access to AI training resources.

Capabilities

Model deployment: Host AI models on a global network of decentralized nodes.
Data marketplaces (coming soon): Facilitate the exchange of training datasets.
Integrated inference services: Provide AI-powered functionality to connected applications.

Outcome: A distributed infrastructure for building and monetizing AI-powered dApps, with compute and data resources accessible to developers worldwide.

By combining these specialized layers with broader AI tooling and agent frameworks, builders can tap into a growing onchain AI ecosystem that spans autonomous execution, decentralized compute, and global-scale AI infrastructure.

Unlock Your Crypto Development With AI Tools

AI is rapidly changing how crypto applications are built. From reducing setup time to generating full-stack logic and deploying secure agents, these tools are reshaping what's possible for solo devs and teams alike.

Rather than replacing developers, AI becomes a force multiplier. It handles the boilerplate so you can solve real protocol design, architecture, and product challenges.

If you're not building with AI, you're building slower. Time to level up.

Ready to build your first AI agent? Visit alchemy.com/ai-agents to get started.

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How to Use AI Tools in Crypto App Development

Understanding Crypto App Development

AI Tools to Integrate Into Your Crypto App Development Workflow

Cursor AI: the IDE That Understands Your Codebase

Key Features of Cursor:

Example: Build a Full Stack dApp with Alchemy Smart Wallets using AI

ChatGPT: Flexible AI Support Across the Stack

Example: Debugging a Smart Contract Error With an AI Prompt

Example: Using AI to Write Ethers.js to Fetch Token Balances

Claude: Deep Context Reasoning AI for Contract Engineering

Example: Audit a Vault Contract using an AI Prompt

Refactoring Example

Lovable: AI Tool for Prompt-to-Frontend with Design System Integration

Example Prompt for AI:

Example Code Output (Wallet.tsx) from AI:

Bolt: One-Prompt Full-Stack dApp Scaffolding Using AI

Example Prompt for AI:

Replit: Real-Time Cloud Dev and AI Automation for Web3

Getting Started with Solidity

Prompt:

Use Replit AI to Write Code for Monitoring and Webhooks with Node.js

Deploy Backend Services

AI Tooling for Error Handling in Smart Contracts and Backends

Smart Contract Example with Revert Logging

Backend Logging Example

Chaining AI Tools Together in a Workflow

Troubleshooting Scenarios Using AI tools

Alchemy Smart Wallet Not Displaying or Initializing Properly

Building Onchain AI Workflows with Alchemy Infra and MCP

What These Tools Enable for Devs

What’s Model Context Protocol (MCP)?

Supported MCP Methods (AI-Callable)

Getting Onchain Data Using MCP-Connected AI

Using MCP Inspector for Debugging

Real-World Use Case: Onchain AI Layers

Virtuals Protocol

Gensyn

Gaia Network

Unlock Your Crypto Development With AI Tools

Alchemy Newsletter

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