different document types at a time. And let's say, for example, that you're trying to build an AI agent, you can also use the Docling MCP server. So, this allows us to automate things with our AI agent and give it the capabilities that Docling has through that model context protocol and allow us to standardize the communication between, say, for example, Claude Coder Continue in our developer CLI to the MCP server, which can handle the document processing for us without us having to know all of those different arguments and commands. So, it makes it quite easy. And the example I show here is by using one of the Claude models on my own Mac itself and connecting this to my VS Code instance. So, let's understand the tools that are available. For the MCP server, we have conversion tools, generation tools, say, for example, if I want to process a specific part of a PDF, and manipulation tools. And this is all provided to the LLM and the agent that we're going to be using with the MCP server. So, here I'm just checking that my local MLX server to run an LLM that's running, and it looks like we've got Quinn 3.6 here. And we're going to verify that the Docling MCP server is also running, which would be done using UVX here. And so, we'll do that in this cell here to make sure that the MCP server is available. Now, in Claude Coder or Codex or another type of AI application, we're going to install the extension. So, for us, this means adding an MCP server in the config.yaml. And now, at this point, we can use a model and an MCP server to do things such as, "Hey, convert this document and give me a summary." Or, create a document with a section of action items and pull in a list from another PDF and export that as markdown. So, we can use all of those Docling components through the MCP server in order to agentically process and parse these documents using an AI agent like Cursor or Claude Code or one of the many open-source options