AI enablement

Layers provides multiple ways for AI agents and tools to access documentation and integrate with the platform.

llms.txt

You can access the documentation in a structured, AI-friendly format at /llms.txt. The file gives an overview of the platform and API in a format suited to large language models.

const response = await fetch('https://docs.uselayers.com/llms.txt');
const content = await response.text();

Markdown and text URLs

Append .md or .txt to any documentation URL to retrieve the page content in plain text format. Use these URLs to access and process the documentation programmatically.

// Access any page as markdown
const response = await fetch('https://docs.uselayers.com/introduction.md');
const markdown = await response.text();

// Or as plain text
const textResponse = await fetch('https://docs.uselayers.com/introduction.txt');
const text = await textResponse.text();

The .md and .txt suffixes work for all documentation pages, including:

API reference pages
Platform guides
Integration documentation

MCP servers

Layers provides two MCP servers that let AI assistants interact directly with your stores:

Layers MCP Server — Full store management with 48 tools for catalog, merchandising, search tuning, metrics, and more. Authenticates via OAuth.
Storefront MCP Server — Read-only storefront operations for search, browse, and recommendations. Authenticates with your storefront API token.

See the MCP servers guide for connection instructions, available tools, and usage examples.

Documentation MCP

You can also access Layers documentation through MCP at https://docs.uselayers.com/mcp. The documentation MCP endpoint provides structured access to the docs for AI tools that need to look up feature details or API reference information.

Use cases

Layers AI enablement features support these workflows:

Store management: Use AI assistants to create merchandising rules, tune search behavior, build sort orders, and analyze metrics through MCP
Storefront integration: Build AI-powered product discovery into customer-facing experiences
Documentation search: AI agents can find relevant information across the docs
Code generation: LLMs can reference accurate API documentation when generating integration code
Development tools: Integrate Layers documentation into your IDE or development workflow

Next steps

Connect MCP servers to manage stores and query storefronts through AI assistants
Explore the API reference to understand available endpoints
Learn about Shopify integration for e-commerce use cases
Review LayersQL for advanced querying capabilities

Overview

SDK Reference

SDK Guides

Changelog & Upgrades

AI enablement

llms.txt

Markdown and text URLs

MCP servers

Documentation MCP

Use cases

Next steps

​llms.txt

​Markdown and text URLs

​MCP servers

​Documentation MCP

​Use cases

​Next steps

llms.txt

Markdown and text URLs

MCP servers

Documentation MCP

Use cases

Next steps