Connecting AI to tax automation: How Avalara model context protocol servers bridge the gap

When Anthropic introduced the model context protocol (MCP) in November 2024, it opened a new chapter in how large language models (LLMs) connect with the world. The MCP is quickly becoming a leading open standard for linking AI systems to external data sources and business applications. Think of it as a universal connector that helps AI talk to everything, including CRMs, ERPs, and compliance systems.

Instead of every company building one-off integrations, the MCP provides a common language. It defines how AI clients can safely discover, understand, and use external tools or APIs — all through a consistent, standardized interface. In short, the MCP helps AI applications access the right data at the right time, without reinventing the wheel each time.

Avalara has long taken an API-first approach to compliance automation. Our APIs power solutions that automate the end-to-end workflow for tax calculation, exemption certificate management, returns filing, tariff-code classification, 1099 and W-9 reporting, tax registrations, business licenses, and e-invoicing.

But as AI becomes part of everyday business software, a new question has emerged: 
How can an AI assistant or agent make sense of APIs without a developer in the loop?

Let’s say an Avalara customer wants to check the filing status of their return. They’d normally need to access the Avalara Portal and locate their return to find the status. An AI agent, on the other hand, lets them ask “what’s the status of our Florida sales tax return?” and will understand natural language and provide a status update. That’s where Avalara MCP servers come in.

Avalara MCP servers act as AI-ready guides to our APIs. They expose clear, machine-readable descriptions of each service — what it does, what inputs it needs, and what kind of information it returns.

When an MCP-compatible AI client connects, it can automatically discover these “tools,” understand how to call them, and interpret the structured results that come back. The AI doesn’t need to guess or hard-code logic; everything it needs to interact with Avalara APIs is described in the protocol itself. So, going back to the above example, when a user asks an ERP-specific AI agent about all tax registrations, the agent will connect to the Avalara AvaTax API through our MCP servers and respond back to the user’s query by providing company-specific nexus information and related tax registration details — all through natural language interaction.

By adopting MCP servers, Avalara is making it easier for AI systems to work directly with our compliance platform. This means developers — and increasingly, business users — can ask complex compliance questions in plain English and have AI agents retrieve accurate answers through our trusted APIs.

It’s another step in our mission to make tax compliance faster, smarter, and more connected — not just for developers, but for anyone who interacts with business systems that depend on Avalara.

Learn more with our developer resources.