We have expanded our developer platform with new capabilities for the DAM REST API and Sales Layer MCP Server, together with a new dedicated MCP section in the public API documentation.

These updates make it easier for development teams and AI-powered tools to work with catalog data and digital assets through Sales Layer APIs.

Expanded DAM REST API

The latest DAM REST API update adds support for non-image files. In addition to working with images, developers can now use the API to manage other digital assets such as documents, spreadsheets, compressed files, presentations, and other files stored in Sales Layer.

The available operations include listing, filtering, creating, retrieving, updating, and deleting files.

The public Sales Layer Postman collection has also been updated with the latest DAM Images and Files operations, making it easier to explore and test these endpoints.

You can explore the latest Sales Layer API documentation by clicking this link.

Sales Layer MCP Server 1.8.2 and new documentation

The Sales Layer MCP Server 1.8.2 is now integrated with the Catalog and DAM REST APIs.

The MCP Server provides dedicated tools for working with different areas of Sales Layer, including:

• Products
• Categories
• Variants
• Custom Entities
• Attribute Sets
• Layouts
• Changelogs
• Images
• Files

This allows MCP-compatible AI clients and development tools to interact with Sales Layer catalog and DAM information using dedicated Sales Layer tools.

A complete section dedicated to the Sales Layer MCP Server is now available in our public developer documentation. It includes:

• Getting started with the MCP Server
• Authentication and permissions
• Available MCP tools
• Troubleshooting
• Local installation
• Practical usage examples

Explore the Sales Layer MCP Server documentation to learn more.

MCP recipes and practical examples

The documentation also includes a dedicated Recipes section with practical examples of queries and tasks that can be performed using the Sales Layer MCP Server.

These examples can help you understand how AI assistants can interact with Sales Layer data and provide ideas for building your own MCP workflows.