google-keep-mcp

search_by_label

Search notes in Google Keep by label name. Choose to include archived or trashed notes as needed.

Instructions

Search notes by label name.

Args:
    label_name (str): The label name to filter by (case-insensitive)
    include_archived (bool, optional): Include archived notes in results (default: True)
    include_trashed (bool, optional): Include trashed notes in results (default: False)
    
Returns:
    str: JSON string containing the matching notes with their id, title, text, pinned status, color, labels and timestamps

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": {
      "label_name": "<label_name>"
    },
    "name": "search_by_label"
  }
}

Input Schema

Name	Required	Description	Default
`label_name`	Yes
`include_trashed`	No
`include_archived`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.2.0Jul 13, 2026

TDQS

A4.4/5.0

Behavior4/5

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

No annotations are provided, so the description carries full burden. It discloses case-insensitivity, default values for include_archived and include_trashed, and the return format. However, it does not discuss authentication, rate limits, or potential limitations.

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 extremely concise and well-structured with a clear docstring format (Args and Returns). Every sentence adds value, and it is front-loaded with the core action.

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

Completeness5/5

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

Given the tool has 3 simple parameters and an output schema (whose format is described), the description provides all necessary information for an agent to invoke it correctly. It covers parameters, defaults, and return structure comprehensively.

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 description coverage is 0%, but the description adds rich semantics for all three parameters: label_name is case-insensitive, include_archived defaults True, include_trashed defaults False. This fully compensates for the lack of schema descriptions.

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 tool searches notes by label name, distinguishing it from sibling tools like search_by_keyword. It specifies the action and resource precisely.

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?

The description provides a clear purpose but lacks explicit guidance on when to use this tool versus alternatives (e.g., search_by_keyword, find). No when-not-to-use or behavioral exclusions are mentioned.

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

Deploy Server