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Glama

getHolidays

Retrieves local bank and public holidays across 100+ countries to verify business days.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearYes
country_codeYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A3.7/5.0
Behavior3/5

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

No annotations exist, so the description must carry the behavioral transparency burden. It discloses that the operation is a retrieval (read-only), but it does not mention rate limits, authentication needs, error behavior for invalid country codes, or any other behavioral traits beyond the basic action.

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 a single, concise sentence that immediately states the purpose. It is front-loaded with the action and resource, making it efficient for an agent to parse.

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?

Given the tool's low complexity (two parameters, no output schema, no nested objects), the description is nearly complete. It covers the core functionality, but it could be improved by noting that it returns a list of holiday dates for the given year and country.

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 description coverage is 0%, so the description should compensate by explaining parameter meanings. However, the description does not elaborate on 'year' or 'country_code' beyond what the parameter names and examples imply. The agent must infer that 'country_code' likely uses ISO 3166-1 alpha-2 codes, but this is not confirmed.

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 identifies the tool's action ('Retrieves'), resource ('local bank and public holidays'), scope ('across 100+ countries'), and purpose ('to verify business days'). It distinguishes itself from sibling tools by naming a specific data domain not covered by others.

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 implies usage for verifying business days, but it does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions or alternative tool names. It is adequate but lacks direct guidance.

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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TDQS

B3/5.0
Disambiguation2/5

Many tools have overlapping functionality, e.g., auditNetworkHost combines DNS, SSL, and header checks that have dedicated tools (auditDnsSecurity, checkSslExpiry, auditSecurityHeaders). Multiple weather and blockchain tools also overlap in scope, making it difficult for an agent to choose the right tool.

Naming Consistency4/5

Most tools follow a consistent verb_noun pattern (e.g., getAirQuality, checkDnsPropagation), but a few deviate (agentPreflight, capabilitiesDiff) and some use compound names (depositCoordinationBounty). Overall, the pattern is clear but not perfectly uniform.

Tool Count1/5

With 56 tools, the server is far too large for a coherent MCP surface. The number suggests a collection of many unrelated APIs rather than a focused tool set. A typical well-scoped server has 3-15 tools.

Completeness2/5

While the tool set covers many domains, each domain has shallow coverage. For example, blockchain tools miss basic transaction sending and contract deployment; weather tools lack forecasts. The 'requestMissingData' endpoint acknowledges gaps, but the current surface is severely incomplete for a general-purpose API.

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