Skip to main content
Layer provides multiple ways for AI agents and tools to access our documentation and integrate with our platform.

​
llms.txt

You can access our documentation in a structured, AI-friendly format at /llms.txt. This file provides a comprehensive overview of our platform and API in a format optimized for large language models. 
const response = await fetch('https://docs.layerci.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. This makes it easy to programmatically access and process our documentation. 
// Access any page as markdown
const response = await fetch('https://docs.layerci.com/introduction.md');
const markdown = await response.text();

// Or as plain text
const textResponse = await fetch('https://docs.layerci.com/introduction.txt');
const text = await textResponse.text();
This works for all documentation pages, including:
  • API reference pages
  • Platform guides
  • Integration documentation

​
MCP server

Layer provides a Model Context Protocol (MCP) server that allows AI assistants to interact with our documentation and services. The MCP server enables:
  • Real-time access to documentation
  • Structured queries about Layer’s features
  • Integration with MCP-compatible AI tools
To connect to our MCP server, configure your AI tool with the Layer MCP endpoint https://docs.uselayers.com/mcp. Refer to your AI tool’s documentation for specific connection instructions.

​
Use cases

These AI enablement features support various workflows:
  • Documentation search: AI agents can quickly find relevant information across our docs
  • Code generation: LLMs can reference accurate API documentation when generating integration code
  • Automated support: Build chatbots that answer questions using up-to-date Layer documentation
  • Development tools: Integrate Layer documentation into your IDE or development workflow

​
Next steps