Zen Planner MCP Server and API by Cotlet

Record attendance in Zen Planner

zen_planner_record_attendance

Read-onlyIdempotent

Record attendance in the user's own Zen Planner account from ChatGPT, Claude or any AI agent. Returns how to do it in Zen Planner step by step (screens, buttons, fields) and opens nothing by itself; then do it with the cotlet_browser_* tools in the user's Zen Planner Cloud Browser. Zen Planner's official API: Yes, but only for partners: Zen Planner has an API on the Daxko Partners portal, and its docs say "Contact your Daxko sales representative to request access" (checked 11 Oct 2026).

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": "zen_planner_record_attendance"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 9, 2026

TDQS

A3.9/5.0

Behavior4/5

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

Beyond the readOnly/openWorld/idempotent annotations, the description adds the crucial behavioral fact that it 'opens nothing by itself' and only returns instructions, plus API access constraints for Zen Planner partners. It does not describe the shape/length of the returned steps, but the safety profile is consistent with and reinforced by the annotations.

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

Conciseness3/5

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

The core mechanic is front-loaded, but the closing sentence about Daxko partner API access and a dated check is tangential justification that does little to help an agent invoke the tool. Cutting it would make the definition tighter without losing invocation-relevant information.

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?

For a zero-parameter guidance tool with no output schema, the description covers what is returned (steps: screens, buttons, fields), that nothing is executed, and the follow-up tooling. It could note prerequisites such as having an open Zen Planner Cloud Browser session, but the essential picture is complete.

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?

There are zero input parameters, so there is nothing for the description to disambiguate; baseline of 4 applies. No misleading parameter expectations are created.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb+resource (record attendance in Zen Planner) and clarifies the actual mechanic: it returns step-by-step screens/buttons/fields rather than performing the action. The verb in the name ('record') could mislead an agent into expecting an executed write, but the second sentence corrects that explicitly.

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?

It states the usage flow clearly: call this to get instructions, then perform the action with cotlet_browser_* tools in the user's Zen Planner Cloud Browser. It does not name when *not* to use it versus siblings like zen_planner_book_class, but the 'get guidance then act via browser' pattern is unambiguous.

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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