A1 Google Calendar MCP

Setup instructions

setup_instructions

Read-onlyIdempotent

Follow step-by-step instructions to connect this server to Google Calendar: create an OAuth client, enable the API, and set client path. Works without credentials; shortens when a client is configured.

Instructions

Step-by-step checklist for connecting this server to Google: creating a Google Cloud project and a Desktop-app OAuth client, publishing the consent screen (mandatory — Testing-mode refresh tokens die after 7 days), downloading the client JSON and handing its PATH to set_client. Works without any credentials; the checklist shortens to 'enable the API + log in' when an OAuth client is already configured (one client serves the whole mcp-google-* line). Never asks the user to paste secrets into the chat.

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": "setup_instructions"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.2.0Sep 20, 2026

TDQS

A4.7/5.0

Behavior5/5

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

Annotations already mark it read-only, idempotent, and non-destructive; the description adds valuable context beyond that: it works without credentials, warns that Testing-mode refresh tokens expire in 7 days, mandates publishing the consent screen, and guarantees it never asks users to paste secrets into the chat. 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.

Conciseness5/5

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

Three dense sentences each carry unique, decision-relevant information: the checklist's contents, the shortened path when already configured, and the no-secrets guarantee. There is no filler or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter instructional tool, the description fully covers purpose, usage timing, workflow relationships, and key behavioral safeguards. The lack of an output schema is acceptable since the tool's job is to present instructions, and the annotations already cover the operational profile.

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?

The input schema is empty and parameter coverage is 100%, so there is nothing for the description to add about parameter semantics. The zero-parameter case earns the baseline 4.

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?

States a specific deliverable: a step-by-step checklist for connecting the server to Google, including project creation, OAuth client, consent screen, and handing the client JSON path to set_client. This clearly distinguishes it from sibling tools like auth_status or set_client.

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?

The description explains when to use it (before credentials exist) and how the checklist shortens when an OAuth client is already configured, referencing set_client as the downstream consumer. It provides clear workflow context, though it does not explicitly say 'use this instead of X' for every alternative.

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