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huebnermarketing

keka-mcp-server

Get Keka Leave Balances

keka_get_leave_balances
Read-onlyIdempotent

Retrieve leave balance breakdown per employee and leave type, showing opening, earned, taken, pending, and closing balances. Optionally filter by employee IDs and select markdown or JSON output.

Instructions

Retrieve leave balances for employees in Keka.

Args:

  • employeeIds (string, optional): Comma-separated employee IDs (omit for all employees)

  • pageNumber (integer): Page number (default: 1)

  • pageSize (integer): Results per page, max 200 (default: 100)

  • response_format ('markdown' | 'json'): Output format (default: 'markdown')

Returns: Leave balance breakdown per employee and leave type — opening, earned, taken, pending, and closing balances.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageSizeNoResults per page (max 200)
pageNumberNoPage number (starts at 1)
employeeIdsNoComma-separated employee IDs (optional)
response_formatNoOutput format: 'markdown' for human-readable, 'json' for machine-readablemarkdown

Schema Changelog

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

  1. First observedv1.0.0

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already mark the tool readOnly, idempotent, and non-destructive, so the description is not burdened with stating safety. It adds useful behavioral context by specifying that omitting employeeIds returns all employees and that the output is a per-employee, per-leave-type breakdown of opening, earned, taken, pending, and closing balances.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a clear one-line purpose followed by Args and Returns sections, making it easy to scan. The Args section repeats schema information somewhat, but the overall length is justified by the parameter details and the return breakdown.

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?

There is no output schema, so the description's Returns section provides the needed high-level response shape: per-employee and per-leave-type balances. It also documents all four parameters with constraints and defaults, leaving no major gap for an agent to call this read-only tool correctly.

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 description coverage is 100%, so the baseline is 3 because the schema already documents all parameters and defaults. The description's Args section mostly duplicates the schema, adding only the useful but minor clarification 'omit for all employees.'

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 opens with a clear verb and resource: 'Retrieve leave balances for employees in Keka.' This distinguishes it from sibling tools like list_leave_requests, list_employees, and get_attendance, so an agent can identify its purpose without ambiguity.

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 when to use the tool by focusing on leave balances, and it notes the optional all-employees behavior via employeeIds. However, it does not explicitly state when to prefer this tool over a sibling, nor does it provide exclusions such as 'use keka_list_leave_requests for request details instead.'

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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