onenote-mcp

onenote_get_notebook_toc

Generate a table of contents for a OneNote notebook to map all sections and pages for quick navigation. Returns a Markdown overview with stats and per-section page lists.

Instructions

Generate a table of contents for a OneNote notebook.

Creates a comprehensive overview of all sections and pages, useful for navigation.

Return Format

Markdown string: "📚 Table of Contents: " with stats and per-section page lists.

Examples

onenote_get_notebook_toc(notebook_id="0-ABC123...")

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": {
      "notebook_id": "<notebook_id>"
    },
    "name": "onenote_get_notebook_toc"
  }
}

Input Schema

Name	Required	Description	Default
`notebook_id`	Yes	The ID of the notebook

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Addedv1.0.4Sep 29, 2026

TDQS

A3.5/5.0

Behavior3/5

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

Annotations are empty, so the description carries the full behavioral burden. It discloses the output format (a Markdown string with stats and per-section page lists), which is useful, but says nothing about read-only safety, authentication requirements, or size/rate limits. Given a mutation-free retrieval tool, this partial disclosure is adequate but incomplete.

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

Conciseness4/5

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

The description is front-loaded with the core purpose and uses clear headers for return format and examples. It is slightly longer than needed for a single-parameter read tool, but every section is scannable and relevant.

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?

An output schema exists, so return values need not be explained, yet the description still summarizes the Markdown return shape, which is helpful. Combined with the example, an agent has enough to call it correctly; only usage routing against siblings is thin.

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?

There is one required parameter with 100% schema description coverage, so the schema already documents notebook_id. The example call shows the expected ID format, adding marginal value, but nothing beyond what the structured fields provide. Baseline 3 applies.

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

Purpose4/5

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

The description states a specific verb and resource ('Generate a table of contents for a OneNote notebook') and clarifies scope by saying it covers 'all sections and pages', which separates it from onenote_get_notebook and the per-level list tools. It stops short of explicitly naming which sibling to prefer, but the aggregation scope is clear.

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?

'Useful for navigation' implies when the tool is helpful, but there is no explicit when-to-use versus onenote_get_notebook, onenote_list_sections, or onenote_list_pages. The agent must infer the choice from the aggregation scope.

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