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m2ai-mcp-servers

Notion Advisor

search

Locate content across all pages and databases in a Notion workspace by keyword or title. Filter results by object type or sort by last edited time to pinpoint the right information.

Instructions

Search across all pages and databases in the workspace. Use when user wants to find content by keyword or title.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch query text
page_sizeNoNumber of results (max 100)
filter_typeNoFilter by object type
sort_directionNoSort by last edited time

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.7/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the workspace-wide search scope and that it matches keyword or title, which gives basic behavioral context. However, it doesn't state whether the operation is read-only, how results are returned, or what limits/defaults apply, leaving noticeable ambiguity.

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 with no filler: the primary action and scope are front-loaded, followed by a direct use-case statement. Every word earns its place, and the length is appropriate for a straightforward search tool.

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

Completeness3/5

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

The tool has four parameters and no output schema or annotations, so the description must provide adequate context for correct invocation. It explains what is searched and when to use it, but it leaves out details like result format, pagination, default sorting, and any implicit limitations, which an agent might need for reliable use.

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 coverage is 100%, so all four parameters are already documented in the input schema. The description adds a slight hint that the query targets keyword or title, which maps to the query parameter, but it adds nothing about page_size, filter_type, or sort_direction. Baseline 3 is appropriate.

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: 'Search across all pages and databases in the workspace.' It also clarifies the intended use ('find content by keyword or title') and the workspace-wide scope. It doesn't explicitly name sibling tools like query_database, but the scope distinction is evident.

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?

The phrase 'Use when user wants to find content by keyword or title' provides a clear trigger condition for invocation. It doesn't explicitly mention alternatives or when not to use the tool, but the context is sufficient for an agent to select it in obvious search scenarios.

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