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Google Workspace MCP Server

Google Workspace MCP Server

by tom275275
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_doc_content

Retrieve the full text content of a Google Doc or Drive file (such as .docx) using its document ID. Returns the document text with a metadata header for easy access.

Instructions

Retrieves content of a Google Doc or a Drive file (like .docx) identified by document_id.

  • Native Google Docs: Fetches content via Docs API.

  • Office files (.docx, etc.) stored in Drive: Downloads via Drive API and extracts text.

Returns: str: The document content with metadata header.

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": {
      "user_google_email": "<user_google_email>",
      "document_id": "<document_id>"
    },
    "name": "get_doc_content"
  }
}

Input Schema

NameRequiredDescriptionDefault
document_idYes
user_google_emailYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.14.3

TDQS

A3.5/5.0
Behavior4/5

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

No annotations are provided, so the description carries the behavioral disclosure burden. It does a good job by explaining that native Docs are fetched via the Docs API, while Office files are downloaded via Drive API and have text extracted, and that the result is a string with a metadata header. It could further disclose edge-case behavior or auth requirements, but the core mechanics are clearly stated.

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 concise, well-structured with bullets, and front-loads the primary action. Every sentence adds useful information, including the API behavior distinctions and the return type. There is no redundant filler.

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?

The tool has only two parameters, and the description covers the retrieval behavior and return value reasonably well. However, because there are no annotations and no schema-level parameter explanations, the missing semantics for user_google_email and the absence of usage alternatives leave the description only partially complete for an agent encountering this tool for the first time.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema provides no descriptions for document_id or user_google_email, and schema description coverage is 0%. The description only clarifies that the file is identified by document_id; it does not explain the role or format of user_google_email, which is a required parameter. This leaves an important parameter under-explained.

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 states a specific verb ('Retrieves content') and resource ('Google Doc or a Drive file like .docx') identified by document_id, and even explains the API path for each file type. It does not explicitly distinguish itself from similar siblings like get_drive_file_content or get_doc_as_markdown, so it falls just short of full sibling differentiation.

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 when the tool is useful by listing supported file types (native Google Docs and Office files in Drive), but it does not explicitly state when to choose this tool over alternatives, nor does it mention any exclusions or limitations. With several overlapping content-retrieval siblings, clearer routing guidance would be valuable.

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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