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Document parsing for AI agents with MCP
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Document parsing for AI agents with MCP

DEV Community: python·Felipe Cardona·about 20 hours ago
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Document parsing for AI agents means giving an agent a tool that turns a PDF, scan or image into text it can read, with the structure kept: headings, tables and reading order. An agent cannot look at a file the way a person does. It reads what a tool returns, so whether it can work with your documents depends on what that tool sends back.

MCP, the Model Context Protocol, is the standard way for an agent to call such tools. A server advertises tools, the agent chooses when to call them, and the results come back as content the model reads. This page explains what that means for documents, describes how providers expose it, and walks through connecting a coding agent to a parsing server and parsing a PDF.

Why an agent needs a parsing tool

A tool call carries JSON, not files. According to the MCP specification , tool results are text, images, audio, resource links or embedded resources, and the model reads them as content.…

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