list_notebooksList the OneNote notebooks in the signed-in user's Microsoft 365 / OneNote account. Returns each notebook's id, display name, created/last-modified times, and whether it is the default notebook. Use to discover a user's OneNote notebooks before browsing sections or pages.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the operation read-only, idempotent, and non-destructive. The description adds useful context beyond those annotations by specifying the exact notebook fields returned and the account-level scope, which matters because there is no output schema. It does not discuss pagination or empty-result behavior, but for a zero-parameter read-only listing tool those are minor gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, with the operation and scope front-loaded, followed by return details and a usage hint. Every clause adds information and there is no filler or restatement of the title.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple, zero-parameter, read-only listing tool, the description is complete enough: it states scope, return fields, and the intended position in the workflow. Annotations cover side effects, and the absence of an output schema is compensated by the explicit return-field list.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and the schema coverage is 100%, so there are no parameter details for the description to clarify; the 0-parameter case is a baseline 4. The description does not invent or imply any undocumented parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description opens with the exact operation ('List the OneNote notebooks'), specifies the account scope ('signed-in user's Microsoft 365 / OneNote account'), and names the returned items. It clearly distinguishes this tool from sibling list_pages and list_sections tools, especially with the phrase 'before browsing sections or pages.'
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
States a clear when-to-use scenario: 'Use to discover a user's OneNote notebooks before browsing sections or pages.' It does not, however, explicitly name sibling tools or state when not to use this tool, so it falls just short of a full 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several tools are genuinely easy to confuse: ask_pipeworx and ask_pipeworx_beta are explicitly described as currently identical, and the five polymarket_* tools overlap significantly in purpose. There are also wrapper-like pairs such as ai_visibility_check vs. scan_competitor_ai_presence and entity_profile vs. recent_changes vs. compare_entities that require reading long descriptions to disambiguate.
The names are mostly lowercase snake_case and readable, but there is no consistent verb_noun pattern: entity_profile and recent_changes are noun phrases, pipeworx_trending and pipeworx_feedback use a prefix, ask_pipeworx_beta is a single-family variant, and scan_competitor_ai_presence uses a different structure from ai_visibility_check. The naming is not chaotic, but it is a mix of conventions.
A server labeled Microsoft Onenote exposes 31 tools, none of which actually relate to OneNote note-taking, notebooks, or pages. Even as a general research/prediction-market server, 31 tools is far above the coherent range, and for the stated product purpose this count is wildly inappropriate.
For the server's declared OneNote domain, there is zero coverage: no tools for creating, reading, updating, or deleting notes, pages, sections, or notebooks. The actual tool surface is centered on Pipeworx data lookups, Polymarket arbitrage, and memory helpers, which leaves the apparent note-taking domain completely unrepresented.