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notion_query_meeting_notes

Search AI meeting notes in a Notion workspace and filter by title or custom criteria, returning newest results first.

Instructions

Find AI meeting notes in the workspace (newest first by default). Read one with notion_read_meeting_notes.

title_contains: simple filter on the meeting title. filter_json: full Notion meeting-notes filter instead, e.g. {"property": "created_time", "filter": {"date_is_after": "2026-10-01"}} or {"operator": "and", "filters": [...]}. Properties: title, attendees, created_time, created_by, last_edited_time, last_edited_by. Overrides title_contains. sort_json: JSON array, e.g. [{"property": "created_time", "direction": "descending"}]. limit: max results (1-50). There is no paging — narrow the filter.

Input Schema

NameRequiredDescriptionDefault
limitNo
sort_jsonNo
filter_jsonNo
title_containsNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.2.2

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses the default ordering, that there is no paging, the hard limit range of 1-50, and that filter_json overrides title_contains. It omits permission/sharing scope (what 'workspace' covers) and rate/volume caveats, so not a 5.

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?

Purpose and the read-next pointer are front-loaded in two short sentences, then a compact per-parameter block. The JSON examples are the only verbosity and they earn their place by disambiguating a free-form string parameter.

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 no explanation, and the description covers query mechanics, override behavior, and the no-pagination constraint. The remaining gap is authorization/scope: nothing says whether results span the whole workspace or only pages shared with the integration.

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

Parameters5/5

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

Schema coverage is 0%, so the description must document all four parameters, and it does: title_contains as a simple title filter, filter_json with two concrete shapes and an enumerated property list, sort_json with an array example, and limit's 1-50 bound. The override precedence between filter_json and title_contains is a detail found nowhere in the 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?

States a specific verb and resource ("Find AI meeting notes") plus a default scope ("workspace", "newest first by default"). It also names the read-one counterpart, so an agent can distinguish it from notion_read_meeting_notes and from the generic notion_query_database sibling.

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

Usage Guidelines4/5

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

"Read one with notion_read_meeting_notes" explicitly routes the agent to the alternative after a list operation, which is the correct two-step pattern. It does not state exclusions (e.g., when to prefer notion_search_pages), so it stops short of a full when/when-not set.

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