Build with Avalara using AI

Build Avalara integrations faster with AI

Use tools like ChatGPT, Claude, and Copilot to generate tax calculation logic, debug API errors, and understand Avalara workflows.

Avalara provides AI-friendly documentation and tooling, like MCP server, llms.txt and Markdown documentation, to improve accuracy and keep responses aligned with current APIs.

What you can build with AI

Generate tax calculation integrations

Debug API errors and improve reliability

Understand tax workflows

Build prototypes and internal tools

Accelerate onboarding for new developers

Getting started

Explore the Avalara Dev Documentation MCP server
Use Markdown documentation in your prompts
Build your first Avalara integration with AI

Best practices

Be specific in prompts

Include language, use case, and API details

Use Markdown (.md) links

Improve parsing and output quality

Use MCP for real-time context

Improve accuracy and reduce hallucinations

Provide context when debugging

Include request payloads and error messages

Validate before production

Test API calls and verify results

Example workflow

Describe your use case to an AI assistant
Generate integration code using Avalara APIs
Use MCP to retrieve API details
Debug errors with AI
Refine and deploy