Skip to main content
Glama
Sign In
google-docs-mcp

google-docs-mcp

by dbuxton
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

docs_get

Retrieve a Google Doc as structured JSON, including title, paragraphs with style and indices, and full text. Use it before editing to understand the document layout.

Instructions

Read a Google Doc and return its structure as JSON.

Returns title, list of paragraphs (with text, style, start/end indices), and the full plain text. Use this before editing to understand the document.

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": {
      "doc_id": "<doc_id>"
    },
    "name": "docs_get"
  }
}

Input Schema

NameRequiredDescriptionDefault
doc_idYesGoogle Doc ID (from the URL: /document/d/{DOC_ID}/edit)

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.3/5.0
Behavior4/5

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

No annotations are provided, so the description carries the burden. It clearly signals a read-only operation by saying 'Read' and 'before editing,' and describes the returned content. It does not mention auth requirements or potential limitations, but for a simple read tool the core behavior is transparent.

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 concise, well-structured sentences: the first states the purpose, the second gives output details and usage context. There is no redundant or vague wording.

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?

The tool is simple, has only one parameter, and an output schema exists. The description covers purpose, return contents, and recommended usage, so an agent has enough context to select and invoke the tool correctly.

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 description coverage is 100% and the sole parameter doc_id is already well documented with URL extraction guidance. The description adds no parameter-level detail, but none is needed because the schema fully covers it.

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 verb ('Read a Google Doc') and resource ('Google Doc'), and clarifies the output is JSON structure. This clearly distinguishes it from sibling editing, commenting, creation, and listing tools.

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?

Explicitly says to use it 'before editing to understand the document,' which gives clear context for when it is appropriate. It does not explicitly name alternatives or exclusions, but the read-versus-edit relationship to siblings is clear.

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

Deploy Server

Other Tools