Skip to main content
Glama

WhenMeet.me

by me.whenmeet

find_common_slots

Read-only

Rank the best meeting times for the given participants, merging live Google/Microsoft calendar data, hand-marked availability and the heat-map sources. Each participant is filtered (Mon–Fri, waking hours) and scored in their OWN timezone; scores factor in buffer time around existing meetings and prefer sooner slots. Returns up to 8 slots: everyone-free slots first (allFree:true), then — only if there are too few — the best compromise slots (allFree:false) with a freeCount. Defaults to the next 14 days. Requires authentication.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoWindow end, unix ms. Default: now + 14 days.
tzNoRequester IANA zone, e.g. Europe/Warsaw — the fallback zone for participants whose own timezone is unknown, and the zone for the round-hour scoring bonus.
fromNoWindow start, unix ms. Default: now.
durationMinNoMeeting length. Default 30.
participantsYesParticipant emails (the authenticated user is the host and should be included).

Schema Changelog

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

  1. Changed1 schema field changed
    • changedInput schema / properties / tz / description
      Previous value: -"IANA zone for business-hours filtering, e.g. Europe/Warsaw."New value: +"Requester IANA zone, e.g. Europe/Warsaw — the fallback zone for participants whose own timezone is unknown, and the zone for the round-hour scoring bonus."
  2. First observed

TDQS

A4.3/5.0
Behavior5/5

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

The description discloses key behaviors beyond the readOnlyHint annotation: merging calendars, hand-marked and heat-map sources, filtering Mon-Fri waking hours, per-timezone scoring, buffer time, preference for sooner slots, and return structure (max 8 slots, allFree then compromise). No contradiction with annotations.

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 efficient with about four sentences, front-loading the purpose. Every sentence adds value, though slightly more structure (e.g., bullet points) could improve scannability.

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 complexity (5 params, no output schema), the description covers algorithm, filters, scoring, and return format adequately. Missing error handling or exact output schema details, but sufficient for agent understanding.

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

Parameters4/5

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

Schema coverage is 100%, but the description adds meaning by explaining the role of tz (fallback zone and scoring bonus), that participants include the host, and the default values for from/to and durationMin.

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 'Rank the best meeting times for the given participants,' which is a specific verb and resource. It distinguishes from siblings like suggest_time and get_meeting_availability by mentioning merging multiple data sources and scoring logic.

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 context such as default window and authentication requirement, but does not explicitly state when to use this tool versus alternatives like suggest_time or get_meeting_availability. Usage is implied but not guided with exclusions.

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

All WhenMeet.me toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.2/5.0
Disambiguation5/5

Each tool targets a distinct operation—creation, slot finding, manual availability management, meeting details, and suggestion handling. No two tools have overlapping purposes.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case (e.g., create_meeting, find_common_slots, set_manual_availability), making them predictable and easy to differentiate.

Tool Count5/5

With 8 tools, the server covers essential scheduling functionalities (create, find slots, manage availability, handle suggestions) without unnecessary bloat. This count is well-suited for the domain.

Completeness4/5

Core workflows are well-covered: finding slots, creating meetings, suggesting/responding to alternate times. Minor gaps exist, such as no direct meeting update or cancellation, but these are not critical for typical agent usage.

Resources