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This guide walks you through setting up Kintsugi MCP in your development environment. Once configured, your AI coding assistant will understand Kintsugi’s API endpoints and help you build integrations faster with accurate code generation.

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Prerequisites

Before setting up Kintsugi MCP, ensure you have:
1

Development Environment

Choose an IDE or editor that supports MCP:
  • Cursor IDE (recommended - native MCP support)
  • Claude Desktop (for general API help)
  • VS Code (with MCP extension)
2

Kintsugi Account

Sign up for a Kintsugi account at app.trykintsugi.com if you haven’t already.
3

API Key & Organization ID

Generate an API key and get your Organization ID from your Kintsugi dashboard:
  1. Navigate to Settings → API Keys
  2. Click Create API Key
  3. Copy and securely store your API key
  4. Find your Organization ID in the lower left-hand corner of the dashboard
Keep Your Credentials Secure - Treat your API key like a password. Never commit it to version control or share it publicly. Use environment variables or secure secret management.Authentication Format: Kintsugi uses API key authentication via headers (not bearer token). You need both:
  • x-api-key header with your API key
  • x-organization-id header with your organization ID

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Cursor IDE Setup

Cursor IDE has native MCP support, making it the best choice for developers building Kintsugi integrations.

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Configuration Steps

1

Open Cursor Settings

Navigate to Settings → Features → MCP Servers (or search for “MCP” in settings)
2

Add Kintsugi MCP Server

Click Add Server or + and configure:
  • Name: kintsugi
  • URL: https://docs.trykintsugi.com/mcp
  • Description: “Kintsugi Tax API endpoints and documentation”
3

Configure Authentication (Optional)

If you want AI to test endpoints, add your credentials:
  • Environment Variables:
    • KINTSUGI_API_KEY=your-key-here
    • KINTSUGI_ORGANIZATION_ID=your-org-id
  • Or configure in MCP server settings if supported
Only add API keys if you want AI to make actual API calls. For code generation only, API keys aren’t required.Note: Kintsugi requires both API key and Organization ID in headers (x-api-key and x-organization-id), not bearer token authentication.
4

Restart Cursor

Restart Cursor IDE to load the MCP configuration.
5

Verify Setup

Open Cursor’s AI chat and ask:
  • “What Kintsugi API endpoints are available?”
  • “Show me how to call the tax estimation endpoint”
The AI should understand Kintsugi’s API structure and provide accurate code examples.

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Using Kintsugi MCP in Cursor

Once configured, here’s how to use it:
  • Code Generation
  • API Documentation
  • Debugging
  • Refactoring
You: “Generate code to calculate tax using Kintsugi API”Cursor AI: Understands /v1/tax/estimate endpoint and generates working code with correct request format.

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Claude Desktop Setup

Claude Desktop can help with API integration code, even when you’re not in an IDE.

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Configuration Steps

1

Locate Config File

Find your Claude Desktop configuration file:
  • macOS
  • Windows
  • Linux
~/Library/Application Support/Claude/claude_desktop_config.json
2

Edit Configuration

Open the config file and add Kintsugi MCP:
{
  "mcpServers": {
    "kintsugi": {
      "url": "https://docs.trykintsugi.com/mcp"
    }
  }
}
If the file doesn’t exist, create it with this structure. If it already has mcpServers, add kintsugi to the existing object.
3

Restart Claude Desktop

Close and reopen Claude Desktop to load the new MCP configuration.
4

Test the Integration

Ask Claude: “What Kintsugi API endpoints can help me build a checkout integration?”Claude should reference Kintsugi’s API endpoints and provide code examples.

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VS Code Setup

VS Code requires an MCP extension to use Kintsugi MCP.

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Using MCP Extensions

  • MCP Extension
  • GitHub Copilot
  1. Install an MCP-compatible extension from VS Code marketplace
  2. Configure Kintsugi MCP server in extension settings
  3. Use AI chat feature with MCP awareness

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Custom MCP Client Setup

For advanced use cases, you can build custom MCP clients or integrate MCP into your own tools.

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Basic MCP Client Example

import { Client } from '@modelcontextprotocol/sdk/client/index.js';
import { SSEClientTransport } from '@modelcontextprotocol/sdk/client/sse.js';

// Create MCP client for Kintsugi
const transport = new SSEClientTransport(
  new URL('https://docs.trykintsugi.com/mcp')
);

const client = new Client({
  name: 'kintsugi-dev-tool',
  version: '1.0.0'
}, {
  capabilities: {
    tools: {}
  }
});

await client.connect(transport);

// List available tools (Kintsugi API endpoints)
const tools = await client.listTools();
console.log('Available Kintsugi endpoints:', tools);

// Use tool to understand an endpoint
const endpointInfo = await client.callTool({
  name: 'get_endpoint_info',
  arguments: {
    endpoint: '/v1/tax/estimate',
    method: 'POST'
  }
});

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Integrating into Development Tools

You can integrate Kintsugi MCP into:
  • Code generators - Auto-generate SDKs and client libraries
  • API testing tools - Auto-generate test cases
  • Documentation generators - Create API docs from MCP schema
  • Custom IDE plugins - Build specialized tools for your team

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Verification and Testing

After setup, verify your MCP integration works correctly:

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Test 1: Endpoint Discovery

Ask your AI: “What Kintsugi endpoints are available for tax calculation?” Expected: AI lists relevant endpoints like /v1/tax/estimate with descriptions.

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Test 2: Code Generation

Ask your AI: “Generate Python code to call Kintsugi’s tax estimation endpoint” Expected: AI generates code with:
  • Correct endpoint URL
  • Proper authentication headers
  • Correct request format
  • Error handling

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Test 3: Schema Understanding

Ask your AI: “What’s the request schema for creating a transaction in Kintsugi?” Expected: AI provides complete schema with:
  • Required fields
  • Optional fields
  • Field types
  • Example values

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Test 4: Debugging Help

Show code with an error: “Why isn’t this working?” (code that’s missing required fields) Expected: AI identifies missing fields and suggests fixes based on actual API schema.

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Best Practices

Let MCP help generate boilerplate code, but always review and customize for your specific needs.
Never store API keys in code or commit them to version control. Use environment variables or secret management.Remember: Kintsugi requires both the API key and Organization ID. Store both securely as x-api-key and x-organization-id headers (not bearer token).
Always test AI-generated code before deploying to production. MCP provides accurate schemas, but you should verify behavior.
Use MCP alongside official documentation. MCP provides quick answers, but docs provide deeper context and examples.
MCP automatically reflects API changes, but always check release notes for breaking changes that might affect your code.

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Troubleshooting

  • Verify MCP server URL is correct
  • Restart your IDE/editor
  • Check MCP server is accessible: visit https://docs.trykintsugi.com/mcp in browser
  • Verify configuration file syntax is valid JSON
  • AI uses current API schema from MCP
  • Check if your API key has correct permissions
  • Verify you’re including both x-api-key and x-organization-id headers
  • Verify you’re using the correct base URL (https://api.trykintsugi.com)
  • Test API calls manually to confirm endpoint behavior
  • Check internet connection
  • Verify MCP server URL is accessible
  • Check for firewall/proxy issues
  • Try accessing the MCP endpoint directly

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Next Steps

Getting Started

Learn how MCP helps you build integrations

Use Cases

See real-world examples and workflows

API Endpoints

Browse all available endpoints

API Reference

Complete API documentation
Ready to Build? Once MCP is configured, you’re ready to build faster. Ask your AI assistant to help with any Kintsugi API integration, and it will understand the endpoints and generate accurate code.