LibreOffice MCP Tools

document_read_text

Extract text content from LibreOffice documents as Markdown for AI processing. Supports pagination and character limits to handle large files efficiently.

Instructions

Read document content as Markdown text. For large documents, use limit/offset for pagination. Default returns up to 4000 characters. Use document_get_outline first to understand structure.

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": {
      "docId": "<docId>"
    },
    "name": "document_read_text"
  }
}

Input Schema

Name	Required	Description
`docId`	Yes	Document handle returned by document_open
`limit`	No	Maximum number of items to return. Default: 50
`offset`	No	Pagination offset. Default: 0
`maxChars`	No	Maximum characters to return. Default: 4000

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Apr 21, 2026

TDQS

A4.4/5.0

Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses key behavioral traits: the output format (Markdown text), pagination support for large documents, default character limit (4000 characters), and a prerequisite suggestion (use document_get_outline first). It doesn't mention error conditions, performance implications, or authentication needs, but covers essential operational context adequately.

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?

The description is three concise sentences with zero waste. The first sentence states the core purpose, the second addresses large documents and pagination, and the third provides a prerequisite recommendation. Each sentence adds critical information, and it's front-loaded with the main functionality.

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?

Given no annotations and no output schema, the description provides good context for a read operation: purpose, usage guidelines, behavioral traits (format, pagination, defaults), and sibling differentiation. It doesn't describe the return value structure (e.g., whether it's a string or object), which is a minor gap since there's no output schema, but overall it's quite complete for the tool's complexity.

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%, so the schema already documents all parameters thoroughly. The description adds minimal value beyond the schema: it implies that limit/offset are for pagination (though the schema says 'items' vs. characters), and mentions the 4000-character default (which matches maxChars default). No additional syntax or format details are provided, meeting the baseline for high schema coverage.

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 clearly states the specific action ('Read document content as Markdown text'), identifies the resource ('document content'), and distinguishes from siblings like document_read_range (which reads specific ranges) and document_get_outline (which provides structure). It goes beyond a simple restatement of the name by specifying the output format (Markdown).

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

Usage Guidelines5/5

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

The description provides explicit guidance on when to use this tool versus alternatives: 'For large documents, use limit/offset for pagination' and 'Use document_get_outline first to understand structure.' It also mentions the default character limit (4000), helping the agent decide when pagination is needed. This directly addresses sibling tools like document_get_outline and document_read_range.

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