DA MCP: Giving AI Assistants Direct Access to Document Authoring

Over the past few months, AI assistants have gone from useful chat tools to something more interesting: agents that can actually do things. They can read files, call APIs, and interact with external systems. Model Context Protocol (MCP) is an open standard that enables AI tools to connect to services in a structured way.

I’ve been working deeply with Document Authoring (DA) — Adobe’s content platform for Edge Delivery Services and I kept thinking about the same question: what if Claude could just talk to DA directly? Not through copy-pasting, not through a browser, but as a first-class tool in a conversation?

So I built it.

What is DA MCP?

DA MCP is a remote MCP server that provides AI assistants such as Claude and ChatGPT with direct access to DA management operations. Once connected, your AI assistant can browse your DA repositories, read and write files, create new pages, move content around, check version history and look up media and fragment references, all without leaving the chat window.

Think of it as giving your AI assistant a command-line-like interface to DA. Instead of switching between tools and copying content back and forth, you can say things like:

Draft a new landing page at /products/overview and save it directly to DA.

Create 5 event pages with details for the provided CSV file.

And it just does it.

The 10 Tools

DA MCP exposes 10 tools covering the full content lifecycle:

Tool	What it does
`da_list_sources`	Browse directories and list files in a repository
`da_get_source`	Read the full content of any file
`da_create_source`	Create a new file with provided content
`da_update_source`	Update an existing file in place
`da_delete_source`	Delete a file
`da_copy_content`	Copy content from one location to another
`da_move_content`	Move or rename content
`da_get_versions`	View version history for a file
`da_lookup_media`	Look up media asset references
`da_lookup_fragment`	Look up content fragment references

How It Works

The server is built in TypeScript and runs on Cloudflare Workers. Authentication uses a token pass-through model, the client sends a DA Admin API token in the Authorization header, which the server forwards to the DA Admin API. If you use the public endpoint at mcp.adobeaemcloud.com, Adobe IMS authentication is handled automatically. No token configuration needed.

The code is open source: github.com/adobe-rnd/da-mcp. Pull requests and feedback welcome.

Getting Connected

Claude.ai is the easiest way to start. Go to Settings → Connectors, find DA MCP, click Connect, and sign in with your Adobe IMS account. Done.

For Claude Desktop, add this to your config file on macOS: ~/Library/Application Support/Claude/claude_desktop_config.json, on Windows: %APPDATA%\Claude\claude_desktop_config.json:

{
  "mcpServers": {
    "da-mcp": {
      "type": "streamable-http",
      "url": "https://mcp.adobeaemcloud.com/adobe/mcp/da"
    }
  }
}

For VS Code or Cursor, add to .vscode/mcp.json:

{
  "mcpServers": {
    "da-mcp": {
      "url": "https://mcp.adobeaemcloud.com/adobe/mcp/da"
    }
  }
}

What I’ve Been Using It For

I’ve been using this daily for a few weeks. The obvious use case is drafting and saving without leaving the chat, which works as expected. It actually saves time with bulk updates across multiple pages; writing a one-off script for that would be tedious. da_get_versions is handy too, mostly because checking file history used to mean a context switch I’d often skip.

For my Adobe Summit 2026 Lab, I wrote most of the lab workbook directly in da.live with the help of Claude and the DA MCP. Here, I took on the role of content author and was able to put the solution through its paces.

A Real-World Example

A colleague posted a good example on LinkedIn: Auditing Summit Labs for missing content pages and creating them from a CSV export in a single conversation saves around 6 hours of manual work. This is the kind of multi-step workflow where having Claude directly connected to DA really pays off.