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gg-mcp

gg-mcp

by tannht
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

read_spreadsheet

Read data from a Google Sheets spreadsheet by providing the spreadsheet ID and optional range (e.g., 'Sheet1!A1:D10').

Instructions

Read data from a Google Sheets spreadsheet. Range format: 'Sheet1!A1:D10' or 'Sheet1'.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "spreadsheet_id": "<spreadsheet_id>"
    },
    "name": "read_spreadsheet"
  }
}

Input Schema

NameRequiredDescriptionDefault
spreadsheet_idYes
rangeNoSheet1

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.1.0

TDQS

B3.3/5.0
Behavior2/5

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

With no annotations, the description partially fills the gap by implying a non-destructive read operation. However, it fails to disclose traits like authentication requirements, rate limits, or the structure of the returned data.

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?

The description is extremely concise, using two sentences to convey purpose and a key format detail. No superfluous information.

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

Completeness3/5

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

Given the absence of an output schema and annotations, the description is minimally adequate. It doesn't specify what data is returned (e.g., values only, including formulas or formatting), leaving gaps for a complete understanding.

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?

The description adds meaningful context for the range parameter with examples, compensating for 0% schema coverage. However, it adds nothing for spreadsheet_id beyond its name, leaving a gap in semantics.

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 verb 'Read data' and the resource 'Google Sheets spreadsheet', with a specific format for the range parameter. It effectively distinguishes itself from sibling tools like append_to_spreadsheet or update_spreadsheet, which modify data.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives, such as get_spreadsheet_info for metadata or search_spreadsheets for finding sheets. It lacks explicit context for selection.

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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