doc.page PDF Extraction

get_chunks

Split a PDF into semantic chunks ready for embeddings (RAG). Each chunk carries its text, estimated tokens, starting page, section heading and the source element ids for citation.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "url": "<url>"
    },
    "name": "get_chunks"
  }
}

Input Schema

Name	Required	Description	Default
`url`	Yes	http(s) URL of the PDF to chunk.
`maxTokens`	No	Target chunk size in tokens. Default 512.

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedJul 13, 2026

changedInput schema / properties / maxTokens / description

Previous value: -"Tamaño objetivo de chunk en tokens. Por defecto 512."New value: +"Target chunk size in tokens. Default 512."

changedInput schema / properties / url / description

Previous value: -"URL http(s) del PDF a trocear."New value: +"http(s) URL of the PDF to chunk."

First observedJul 12, 2026

TDQS

A4/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description fully describes what the output contains (text, tokens, page, heading, element IDs). However, it does not mention required permissions, destructive effects, or operational constraints (e.g., file size limits).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, no wasted words, front-loaded with the core action (split PDF into chunks) followed by output details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The output schema is absent, but the description compensates by detailing chunk contents. Lacks error conditions, limits, or prerequisites. For a simple two-parameter tool, it is largely complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% (both url and maxTokens have descriptions). The tool description adds context about output but no additional meaning to the parameters beyond schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses specific verb 'Split' and resource 'PDF into semantic chunks'. It explicitly states the RAG/embeddings use case and distinguishes from siblings like extract_pdf (raw text) and list_tables (tables).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for RAG embeddings but does not provide explicit when-to-use, when-not-to-use, or alternatives. No comparison with sibling tools like extract_pdf.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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