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Glama

Calendly

by io.github.pipeworx-io

List Invitees

list_invitees
Read-onlyIdempotent

List the invitees of a scheduled event by event UUID. Returns invitee names, emails, status (active/canceled), timezone, and answers to booking questions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
uuidYesScheduled event UUID (last segment of the event URI).
countNoNumber of results per page (default 20, max 100).
statusNoFilter invitees by status.
_apiKeyYesCalendly personal access token (sent as Bearer token)
page_tokenNoToken from a previous response for the next page.

Schema Changelog

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

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "_apiKey": "your-calendly-api-key",
+    "uuid": "XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX"
+  },
+  {
+    "_apiKey": "your-calendly-api-key",
+    "count": 25,
+    "status": "active",
+    "uuid": "XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX"
+  }
+]
  2. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations confirm read-only, idempotent, non-destructive behavior. The description adds valuable context about the return fields (names, emails, status, timezone, answers), which annotations do not cover. No contradictions.

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, front-loaded with the core purpose, no unnecessary words.

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 no output schema, the description explains return fields adequately. Could mention pagination but schema already includes pagination parameters. Overall complete for the tool's scope.

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 coverage is 100%, and the description does not add parameter-level details beyond what the schema provides. Baseline 3 applies.

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 lists invitees of a scheduled event by UUID, specifying the return fields (names, emails, status, etc.). It distinguishes from sibling tools like list_scheduled_events and get_event.

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 retrieving invitee details but lacks explicit when-to-use or when-not-to-use guidance, and does not mention alternatives.

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

A3.6/5.0
Disambiguation2/5

Several research tools overlap heavily: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, discover_tools, and suggest_questions all route to the same underlying catalog. Similarly, bet_research, polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, and polymarket_kalshi_spread form a dense prediction-market cluster with fuzzy boundaries. The few Calendly tools are distinct, but they are drowned out by duplicative families.

Naming Consistency3/5

Most names use snake_case and a noun-based pattern (e.g. polymarket_edges, entity_profile), and several follow verb_noun (list_event_types, list_scheduled_events, resolve_entity). But there are standalone verbs (forget, recall, subscribe) and inconsistent verb styles (ask_ vs list_ vs scan_), so the pattern is readable but not predictable.

Tool Count2/5

36 tools is far too many for a server ostensibly named Calendly: only 5 tools relate to Calendly events and invitees, while 31 tools belong to an unrelated Pipeworx data-research platform. The count is bloated by a second domain bolted onto the server, making the surface hard to navigate for its apparent purpose.

Completeness2/5

For the Calendly domain implied by the server name, the surface is missing core operations: there is no create/update/cancel/delete event, no cancel or reschedule flow, no invitee management beyond listing, and no event-type creation or editing. The Pipeworx side is broader, but even it has gaps like no bulk data export or direct raw-tool invocation.

Resources