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himalaya-mcp

himalaya-mcp

by Data-Wise
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

get_unread_count

Retrieve the number of unread emails in a specific folder or across all folders. Uses server-side filtering to provide fast counts even in large mailboxes.

Instructions

Get the number of unread emails in a folder (or across all folders). Uses himalaya's server-side filter for fast counting even in large mailboxes.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_unread_count"
  }
}

Input Schema

NameRequiredDescriptionDefault
folderNoFolder name (default: INBOX)
accountNoAccount name (uses default if omitted)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.0.0

TDQS

A3.8/5.0
Behavior3/5

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

Without annotations, the description carries full burden. It discloses a positive behavioral trait (server-side filter for speed) but omits mention of read-only nature, error handling, or whether counts are real-time. Adequate but lacking in safety details.

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 wasted words. Information about performance and scope is front-loaded.

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?

Given no output schema, the description is fairly complete for a simple count tool. However, the ambiguity on cross-folder counting and lack of error condition details leave gaps.

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

Parameters2/5

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

Schema coverage is 100% with descriptions, but the description introduces ambiguity: it says 'or across all folders' while the schema says folder defaults to INBOX, not all folders. This contradiction reduces clarity beyond what the schema provides.

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 uses the verb 'Get' and specifies the resource 'number of unread emails in a folder (or across all folders)', clearly distinguishing it from sibling tools like list_emails or read_email.

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 description implies when to use by highlighting performance ('fast counting even in large mailboxes'), but does not explicitly state when not to use or compare directly to alternatives like list_emails with filtering.

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

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