MCP Google Workspace Server
The MCP Google Workspace Server enables AI agents to interact with Google Drive, Docs, and Sheets services via the Model Context Protocol.
Capabilities include:
Google Drive: Search files using queries and pagination, create folders with optional parent folders
Google Docs: Create documents with titles and optional content, retrieve and update document content by ID
Google Sheets: Create spreadsheets, retrieve and update cell values using A1 notation range
The server supports multiple transport modes (stdio, SSE, WebSocket), is compatible with MCP clients like Cursor, and requires Google OAuth setup for authentication.
Integrates with Codecov for code coverage reporting
Connects with GitHub for CI workflows and repository management
Provides capabilities to create, read, and update Google Docs documents
Enables searching for files and creating folders in Google Drive
Allows creating spreadsheets and reading/writing cell values in Google Sheets
Publishes the package to PyPI for distribution
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCP Google Workspace Serversearch for budget spreadsheets in my Drive"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP Google Workspace Server
A Model Context Protocol (MCP) server enabling AI agents to interact with Google Workspace (Drive, Docs, and Sheets) services.
π Features
Google Drive: Search files, create folders
Google Docs: Create, read, update documents
Google Sheets: Create spreadsheets, read/write cell values
Multiple transport modes: stdio (default), SSE, WebSocket
MCP-compatible client support (Cursor, etc.)
Related MCP server: MCP Google Suite
π Installation
Using uv (recommended)
uvx mcp-google-suiteUsing pip
pip install mcp-google-suiteDevelopment setup
# Clone and install
git clone git@github.com:adexltd/mcp-google-suite.git && cd mcp-google-suite
uv venv && source .venv/bin/activate # or .venv\Scripts\activate on Windows
uv pip install -e .π§ Configuration
Configure for MCP Clients
Add to your client settings (e.g. Cursor, Claude):
Using uvx (recommended):
{
"mcpServers": {
"mcp-google-suite": {
"command": "uvx",
"args": ["mcp-google-suite"],
"env": {
"GOOGLE_APPLICATION_CREDENTIALS": "~/.google/server-creds.json",
"GOOGLE_OAUTH_CREDENTIALS": "~/.google/oauth.keys.json"
}
}
}
}Using pip installation:
{
"mcpServers": {
"mcp-google-suite": {
"command": "python",
"args": ["-m", "mcp_google_suite"],
"env": {
"GOOGLE_APPLICATION_CREDENTIALS": "~/.google/server-creds.json",
"GOOGLE_OAUTH_CREDENTIALS": "~/.google/oauth.keys.json"
}
}
}
}Google OAuth Setup
Visit Google Cloud Console
Enable Drive, Docs, and Sheets APIs
Create OAuth 2.0 credentials
Save as
~/.google/oauth.keys.jsonRun
mcp-google authto authenticate
Available Tools
Drive Operations
drive_search_files: Search files in Google Drivequery(string, required): Search querypage_size(integer, optional): Number of results to return
drive_create_folder: Create a new foldername(string, required): Folder nameparent_id(string, optional): Parent folder ID
Docs Operations
docs_create: Create a new documenttitle(string, required): Document titlecontent(string, optional): Initial content
docs_get_content: Get document contentdocument_id(string, required): Document ID
docs_update_content: Update document contentdocument_id(string, required): Document IDcontent(string, required): New content
Sheets Operations
sheets_create: Create a new spreadsheettitle(string, required): Spreadsheet titlesheets(array, optional): Sheet names
sheets_get_values: Get cell valuesspreadsheet_id(string, required): Spreadsheet IDrange(string, required): A1 notation range
sheets_update_values: Update cell valuesspreadsheet_id(string, required): Spreadsheet IDrange(string, required): A1 notation rangevalues(array, required): 2D array of values
π οΈ Development
# Install dev dependencies
uv pip install -e ".[dev]"
# Setup pre-commit hooks
pre-commit install
# Run tests
pytest
# Format code
black . && ruff check --fix .π Debugging
Use the MCP Inspector for interactive testing:
# Using uvx
npx @modelcontextprotocol/inspector uvx mcp-google
# For development
cd path/to/mcp-google-suite
npx @modelcontextprotocol/inspector uv run mcp-googleπ Resources
π€ Contributing
Please read CONTRIBUTING.md for details on our code of conduct and the process for submitting pull requests.
π Security
See SECURITY.md for reporting vulnerabilities and best practices.
π License
MIT License - See LICENSE file for details.
Available Tools
8 toolsdocs_createC
Create a new Google Doc
| Name | Required | Description | Default |
|---|---|---|---|
| content | No | Initial content | |
| title | Yes | Title of the document |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states 'Create' which implies a write/mutation operation, but doesn't mention authentication requirements, rate limits, whether the operation is idempotent, or what happens on success/failure. This leaves significant behavioral gaps for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that states the core purpose without any wasted words. It's appropriately sized for a simple creation tool and gets straight to the point.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what happens after creation (e.g., returns a document ID, URL, or metadata), error conditions, or integration with sibling tools. The agent lacks critical context for proper tool invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters ('content' and 'title') adequately. The description doesn't add any parameter-specific context beyond what's in the schema, such as formatting examples or constraints, meeting the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Create') and resource ('Google Doc'), making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling tools like 'sheets_create' or 'drive_create_folder' beyond specifying the resource type, which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 like 'sheets_create' or 'drive_create_folder'. There's no mention of prerequisites, context for creation, or comparison with sibling tools, leaving the agent with minimal usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
docs_get_contentC
Get the contents of a Google Doc
| Name | Required | Description | Default |
|---|---|---|---|
| document_id | Yes | ID of the document |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It states what the tool does but doesn't disclose whether it requires authentication, has rate limits, returns structured or plain text content, or handles errors. This leaves significant gaps for an agent to understand operational constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It is front-loaded with the core purpose, making it easy to parse quickly. Every word earns its place by conveying essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete for a tool that retrieves content. It doesn't explain what 'contents' means (e.g., text, formatting, metadata), the return format, or any prerequisites like needing the document ID upfront. For a read operation with undefined outputs, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the single parameter 'document_id' clearly documented in the schema. The description adds no additional parameter semantics beyond implying the tool operates on a Google Doc, which is already evident from the tool name. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and resource ('contents of a Google Doc'), making the purpose immediately understandable. It distinguishes from siblings like docs_create (creation) and docs_update_content (modification), though it doesn't explicitly contrast with drive_search_files which might also retrieve document content indirectly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. For example, it doesn't mention whether to use this for retrieving full document content versus sheets_get_values for spreadsheet data, or drive_search_files for finding documents first. The description assumes the user already knows when this tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
docs_update_contentC
Update the content of a Google Doc
| Name | Required | Description | Default |
|---|---|---|---|
| content | Yes | New content | |
| document_id | Yes | ID of the document |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states this is an update operation, implying mutation, but doesn't cover critical aspects like required permissions, whether changes are reversible, rate limits, or what happens to existing content not mentioned. This leaves significant gaps for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words, making it highly concise and front-loaded. Every part of the sentence directly contributes to understanding the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is insufficient. It lacks details on behavioral traits (e.g., permissions, side effects), usage context, and output expectations, leaving the agent with incomplete information to operate effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters ('document_id' and 'content') adequately. The description adds no additional meaning beyond implying that 'content' replaces existing content, which is minimal value over what the schema provides, justifying the baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Update') and resource ('content of a Google Doc'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'docs_create' or 'sheets_update_values' beyond mentioning Google Docs specifically.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites (e.g., needing an existing document), exclusions, or comparisons to siblings like 'docs_get_content' for read operations or 'sheets_update_values' for similar updates in Sheets.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
drive_create_folderC
Create a new folder in Google Drive
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Name of the folder | |
| parent_id | No | ID of parent folder |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool creates a folder but doesn't mention whether this requires specific permissions, what happens on duplicate names, if the operation is idempotent, or what the response contains (e.g., folder ID). For a mutation tool with zero annotation coverage, this leaves significant gaps in understanding the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with zero wasted words. It's front-loaded with the core action and resource, making it immediately understandable. Every word earns its place by specifying 'new folder' and 'Google Drive' context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given this is a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., folder metadata or ID), error conditions, or behavioral nuances like permissions required. For a tool that modifies state, this lack of context leaves the agent under-informed about how to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so both parameters ('name' and 'parent_id') are fully documented in the schema. The description adds no additional parameter semantics beyond implying a folder needs a name and parent location. This meets the baseline of 3 when the schema does the heavy lifting, but the description doesn't compensate with extra context like format examples or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Create') and resource ('new folder in Google Drive'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'docs_create' or 'sheets_create', but the 'Google Drive' context provides some implicit distinction. The description avoids tautology by specifying what is being created rather than just restating the tool name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 like 'drive_search_files' for finding existing folders or 'docs_create' for creating documents. There's no mention of prerequisites (e.g., needing parent folder permissions) or exclusions (e.g., not for creating files). The agent must infer usage context solely from the tool name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
drive_search_filesC
Search for files in Google Drive
| Name | Required | Description | Default |
|---|---|---|---|
| page_size | No | Number of results to return | |
| query | Yes | Search query |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. 'Search for files' implies a read operation, but it doesn't disclose behavioral traits like whether it requires authentication, has rate limits, returns paginated results (despite having a page_size parameter), or what happens with empty results. The description adds minimal value beyond the basic action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's appropriately sized and front-loaded, directly stating the tool's purpose without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 2 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what the search returns (e.g., file metadata, IDs, or content), how results are structured, or error conditions. For a search tool with no structured output documentation, this leaves significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters ('query' and 'page_size') adequately. The description doesn't add any meaning beyond what the schema provides, such as query syntax examples or context about result ordering. Baseline 3 is appropriate when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Search for files') and resource ('in Google Drive'), providing a specific verb+resource combination. However, it doesn't differentiate from potential sibling tools like 'drive_create_folder' that might also involve file operations, so it doesn't fully distinguish from alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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. With sibling tools like 'docs_create', 'sheets_get_values', and 'drive_create_folder' available, there's no indication of when searching files is appropriate versus creating or accessing other document types.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sheets_createC
Create a new Google Sheet
| Name | Required | Description | Default |
|---|---|---|---|
| sheets | No | Sheet names | |
| title | Yes | Title of the spreadsheet |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure but only states the basic action. It doesn't mention permissions required, whether creation is reversible, rate limits, or what happens upon success/failure. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's front-loaded with the core action and resource, making it immediately clear. Every word earns its place without redundancy or unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't address behavioral aspects like permissions or side effects, nor does it explain what the tool returns upon success. Given the complexity of creating a resource in Google Sheets, more context is needed for effective agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters ('title' and 'sheets'). The description doesn't add any meaning beyond what the schema provides, such as explaining the relationship between 'title' and 'sheets' or providing examples. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Create') and resource ('a new Google Sheet'), making the purpose immediately understandable. It doesn't distinguish from sibling tools like 'docs_create' or 'drive_create_folder', which would require mentioning it creates specifically spreadsheet files rather than documents or folders.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 like 'docs_create' for documents or 'drive_create_folder' for folders. There's no mention of prerequisites, context, or exclusions, leaving the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sheets_get_valuesC
Get values from a Google Sheet range
| Name | Required | Description | Default |
|---|---|---|---|
| range | Yes | A1 notation range | |
| spreadsheet_id | Yes | ID of the spreadsheet |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool reads values, implying it's non-destructive, but doesn't cover critical aspects like authentication requirements, rate limits, error handling, or what the return format looks like (especially since there's no output schema). This leaves significant gaps for an agent to understand how to use it effectively.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasteβit directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of interacting with Google Sheets (which involves authentication, API constraints, and data formatting), the description is insufficient. With no annotations, no output schema, and minimal behavioral context, it doesn't provide enough information for an agent to use the tool confidently in real-world scenarios, despite the clear schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with both parameters (range and spreadsheet_id) clearly documented in the schema. The description adds no additional meaning beyond the schema, such as examples or context for how these parameters interact. This meets the baseline score of 3 since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get values') and target resource ('from a Google Sheet range'), providing a specific verb+resource combination. However, it doesn't differentiate this tool from potential sibling read operations on sheets (though none exist in the provided sibling list), making it clear but not fully distinctive.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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. It doesn't mention prerequisites (e.g., authentication), compare it to other sheet-related tools like sheets_update_values, or specify scenarios where it's appropriate (e.g., for reading data vs. modifying it).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sheets_update_valuesC
Update values in a Google Sheet range
| Name | Required | Description | Default |
|---|---|---|---|
| range | Yes | A1 notation range | |
| spreadsheet_id | Yes | ID of the spreadsheet | |
| values | Yes | 2D array of values |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool updates values but doesn't explain critical behaviors: whether this overwrites existing data, requires specific permissions, has rate limits, or what happens on success/failure. For a mutation tool with zero annotation coverage, this leaves significant gaps in understanding how the tool operates.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It front-loads the core purpose ('Update values in a Google Sheet range') without unnecessary elaboration. Every word earns its place, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given this is a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't cover behavioral traits (e.g., overwrite behavior, error conditions), return values, or usage context. While the schema fully describes parameters, the overall tool understanding remains inadequate for safe and effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all three parameters (range, spreadsheet_id, values) with basic descriptions. The description adds no additional semantic context about parameters, such as format examples for 'A1 notation' or what constitutes valid values in the 2D array. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Update values') and resource ('in a Google Sheet range'), making the tool's purpose immediately understandable. It distinguishes itself from siblings like sheets_create and sheets_get_values by focusing on updating existing data rather than creating new sheets or retrieving values. However, it doesn't specify what type of values can be updated or how the update behaves, which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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. It doesn't mention prerequisites (e.g., needing an existing spreadsheet), exclusions (e.g., not for creating new sheets), or comparisons to sibling tools like sheets_create or sheets_get_values. The agent must infer usage from the name and context alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
8 tool updates
v1.0.0- First observed
docs_create - First observed
docs_get_content - First observed
docs_update_content - First observed
drive_create_folder - First observed
drive_search_files - First observed
sheets_create - First observed
sheets_get_values - First observed
sheets_update_values
TDQS
Every tool has a clearly distinct purpose with no ambiguity, as each is scoped to a specific Google Workspace service (Docs, Drive, Sheets) and action (create, get/read, update, search). The naming prefixes (docs_, drive_, sheets_) immediately differentiate the domains, preventing misselection.
All tools follow a consistent verb_noun pattern with service prefixes, using snake_case uniformly (e.g., docs_create, sheets_update_values). This predictable naming scheme makes it easy for an agent to understand and navigate the toolset without confusion.
With 8 tools, the count is well-scoped for covering core operations across three Google Workspace services. Each tool earns its place by providing essential CRUD-like functionality (create, get, update) and search capabilities, avoiding bloat while ensuring practical coverage.
The toolset offers strong coverage for Docs, Drive, and Sheets with create, read, update, and search operations, but minor gaps exist, such as missing delete operations for Docs and Sheets, and no update for Drive folders. Agents can work around these gaps, but the surface isn't fully complete for full lifecycle management.
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