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erickva

Google Calendar - No deletion

by erickva
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Remote

Google Workspace MCP Server

A Model Context Protocol (MCP) server that provides tools for interacting with Gmail and Calendar APIs. This server enables you to manage your emails and calendar events programmatically through the MCP interface.

Features

Gmail Tools

  • list_emails: List recent emails from your inbox with optional filtering

  • search_emails: Advanced email search with Gmail query syntax

  • send_email: Send new emails with support for CC and BCC

  • modify_email: Modify email labels (archive, trash, mark read/unread)

Calendar Tools

  • list_events: List upcoming calendar events with date range filtering

  • create_event: Create new calendar events with attendees

  • The events below were removed from this server for security measures since Google Cloud Calendar API does not have a scope that allows creation but prevents deletion or updates.

  • update_event: Update existing calendar events

  • delete_event: Delete calendar events

Related MCP server: google-workspace-mcp-server

Prerequisites

  1. Node.js: Install Node.js version 14 or higher

  2. Google Cloud Console Setup:

    • Go to Google Cloud Console

    • Create a new project or select an existing one

    • Enable the Gmail API and Google Calendar API:

      1. Go to "APIs & Services" > "Library"

      2. Search for and enable "Gmail API"

      3. Search for and enable "Google Calendar API"

    • Set up OAuth 2.0 credentials:

      1. Go to "APIs & Services" > "Credentials"

      2. Click "Create Credentials" > "OAuth client ID"

      3. Choose "Web application"

      4. Set "Authorized redirect URIs" to include: http://localhost:4100/code

      5. Note down the Client ID and Client Secret

Setup Instructions

Installing via Smithery

To install Google Workspace Server - No Calendar Deletion for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @erickva/google-workspace-mcp-server-no-calendar-deletetion --client claude

Installing Manually

  1. Clone and Install:

    git clone https://github.com/epaproditus/google-workspace-mcp-server.git
cd google-workspace-mcp-server
npm install

  2. Create OAuth Credentials: Create a credentials.json file in the root directory:

    {
    "web": {
        "client_id": "YOUR_CLIENT_ID",
        "client_secret": "YOUR_CLIENT_SECRET",
        "redirect_uris": ["http://localhost:4100/code"],
        "auth_uri": "https://accounts.google.com/o/oauth2/auth",
        "token_uri": "https://oauth2.googleapis.com/token"
    }
}

  3. Get Refresh Token:

    node get-refresh-token.js

    This will:

    • Open your browser for Google OAuth authentication

    • Request the following permissions:

      • https://www.googleapis.com/auth/gmail.modify

      • https://www.googleapis.com/auth/calendar

      • https://www.googleapis.com/auth/gmail.send

    • Save the credentials to token.json

    • Display the refresh token in the console

  4. Configure MCP Settings: Add the server configuration to your MCP settings file:

    • For VSCode Claude extension: ~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json

    • For Claude desktop app: ~/Library/Application Support/Claude/claude_desktop_config.json

    Add this to the mcpServers object:

    {
  "mcpServers": {
    "google-workspace": {
      "command": "node",
      "args": ["/path/to/google-workspace-server/build/index.js"],
      "env": {
        "GOOGLE_CLIENT_ID": "your_client_id",
        "GOOGLE_CLIENT_SECRET": "your_client_secret",
        "GOOGLE_REFRESH_TOKEN": "your_refresh_token"
      }
    }
  }
}

  5. Build and Run:

    npm run build

Usage Examples

Gmail Operations

  1. List Recent Emails:

    {
  "maxResults": 5,
  "query": "is:unread"
}

  2. Search Emails:

    {
  "query": "from:example@gmail.com has:attachment",
  "maxResults": 10
}

  3. Send Email:

    {
  "to": "recipient@example.com",
  "subject": "Hello",
  "body": "Message content",
  "cc": "cc@example.com",
  "bcc": "bcc@example.com"
}

  4. Modify Email:

    {
  "id": "message_id",
  "addLabels": ["UNREAD"],
  "removeLabels": ["INBOX"]
}

Calendar Operations

  1. List Events:

    {
  "maxResults": 10,
  "timeMin": "2024-01-01T00:00:00Z",
  "timeMax": "2024-12-31T23:59:59Z"
}

  2. Create Event:

    {
  "summary": "Team Meeting",
  "location": "Conference Room",
  "description": "Weekly sync-up",
  "start": "2024-01-24T10:00:00Z",
  "end": "2024-01-24T11:00:00Z",
  "attendees": ["colleague@example.com"]
}

3. Update Event:

{
  "eventId": "event_id",
  "summary": "Updated Meeting Title",
  "location": "Virtual",
  "start": "2024-01-24T11:00:00Z",
  "end": "2024-01-24T12:00:00Z"
}

4. Delete Event:

{
  "eventId": "event_id"
}

Troubleshooting

  1. Authentication Issues:

    • Ensure all required OAuth scopes are granted

    • Verify client ID and secret are correct

    • Check if refresh token is valid

  2. API Errors:

    • Check Google Cloud Console for API quotas and limits

    • Ensure APIs are enabled for your project

    • Verify request parameters match the required format

License

This project is licensed under the MIT License.

Available Tools

7 tools
create_eventC

Create a new calendar event

ParametersJSON Schema
NameRequiredDescriptionDefault
attendeesNoList of attendee email addresses
descriptionNoEvent description
endYesEnd time in ISO format
locationNoEvent location
startYesStart time in ISO format
summaryYesEvent title

TDQS

C2.9/5.0
Behavior2/5

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 this is a creation operation but doesn't mention permissions required, whether it sends invitations to attendees, error conditions, or what happens on success/failure. 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.

Conciseness5/5

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

The description is a single, efficient sentence that gets straight to the point with zero wasted words. It's appropriately sized for a straightforward creation tool and front-loads the essential information.

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

Completeness2/5

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 event ID, sends notifications), error handling, or behavioral nuances. The 100% schema coverage helps with parameters but doesn't compensate for the lack of operational context.

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 schema description coverage is 100%, with all parameters well-documented in the schema itself. The description adds no additional parameter information beyond what's already in the structured fields, so it 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.

Purpose4/5

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 ('calendar event'), making the purpose immediately understandable. However, it doesn't differentiate this tool from potential sibling tools like 'modify_email' or 'meeting_suggestion' that might also involve calendar operations, preventing 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.

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. Given sibling tools like 'list_events' and 'meeting_suggestion', there's no indication of whether this is for manual creation versus automated suggestions, or any prerequisites for use.

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

list_emailsC

List recent emails from Gmail inbox

ParametersJSON Schema
NameRequiredDescriptionDefault
maxResultsNoMaximum number of emails to return (default: 10)
queryNoSearch query to filter emails

TDQS

C2.9/5.0
Behavior2/5

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 mentions 'recent emails' but doesn't specify what 'recent' means (e.g., time frame, ordering), whether it's read-only or has side effects, or any rate limits or authentication needs. This leaves significant gaps for an agent to understand 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.

Conciseness5/5

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

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, making it easy to parse quickly.

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

Completeness2/5

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

Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'recent' entails, the return format (e.g., list structure, fields), or how it differs from sibling tools like 'search_emails'. For a tool with 2 parameters and no structured behavioral hints, more context is needed.

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%, so the schema already documents both parameters ('maxResults' and 'query') with their types and default values. The description adds no additional parameter semantics beyond what the schema provides, meeting the baseline for high coverage.

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 clearly states the action ('List') and resource ('recent emails from Gmail inbox'), making the tool's purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'search_emails' or 'modify_email' beyond the basic verb, missing explicit distinction.

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?

No guidance is provided on when to use this tool versus alternatives like 'search_emails' or 'modify_email'. The description implies a default listing of recent emails but offers no context on prerequisites, exclusions, or specific use cases.

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

list_eventsC

List upcoming calendar events

ParametersJSON Schema
NameRequiredDescriptionDefault
maxResultsNoMaximum number of events to return (default: 10)
timeMaxNoEnd time in ISO format
timeMinNoStart time in ISO format (default: now)

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action but doesn't mention permissions required, rate limits, pagination behavior, or what 'upcoming' means (e.g., default time range). This leaves significant gaps for a read operation with no structured safety hints.

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 a single, efficient sentence that directly states the tool's purpose without any wasted words. It's appropriately sized and front-loaded, making it easy to parse quickly.

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

Completeness2/5

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

Given the lack of annotations and output schema, the description is incomplete for a tool with three parameters and no safety hints. It doesn't explain what 'upcoming' entails, the return format, or error handling, leaving the agent with insufficient context to use the tool effectively beyond basic invocation.

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 schema description coverage is 100%, so the input schema fully documents the three parameters (maxResults, timeMax, timeMin) with their types and defaults. The description adds no additional parameter semantics beyond implying a time-based filter through 'upcoming', which aligns with the schema but doesn't provide extra value.

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 'List upcoming calendar events' clearly states the verb ('List') and resource ('upcoming calendar events'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'create_event' or 'meeting_suggestion' beyond the basic action, 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.

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. With siblings like 'create_event' and 'meeting_suggestion' available, there's no mention of when to choose listing events over creating them or using the suggestion tool, leaving usage context unclear.

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

meeting_suggestionC

Suggest available meeting slots within the next 30 days

ParametersJSON Schema
NameRequiredDescriptionDefault
bankHolidaysNoList of bank holiday dates in YYYY-MM-DD format
calendarIdsNoList of Google Calendar IDs (default: ["primary"])
daysToSearchNoNumber of days to find slots for (default: 3)
meetingLengthMinutesNoMeeting length in minutes (default: 60)
slotsPerDayNoNumber of slots per day to suggest (default: 1)
timezoneNoTimezone for scheduling (default: America/Sao_Paulo)
workingHoursEndNoEnd of working hours (24h format, default: 17)
workingHoursStartNoStart of working hours (24h format, default: 9)

TDQS

C2.9/5.0
Behavior2/5

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 mentions the 30-day constraint but doesn't explain what 'suggest' entails (e.g., how slots are determined, whether it considers existing events, authentication needs, rate limits, or what the output looks like). For a tool with 8 parameters and no annotation coverage, this leaves significant gaps.

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 a single, efficient sentence that gets straight to the point with zero wasted words. It's appropriately sized and front-loaded with the core functionality.

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

Completeness2/5

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

For a tool with 8 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain the suggestion algorithm, how parameters interact, what the return format is, or error conditions. The 30-day mention provides some context but doesn't compensate for the missing behavioral and output information.

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 doesn't add any parameter-specific information beyond what's already in the schema (which has 100% coverage). It mentions 'within the next 30 days' which relates to the time scope but doesn't clarify how this interacts with parameters like 'daysToSearch'. Baseline 3 is appropriate 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.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Suggest available meeting slots within the next 30 days' - a specific verb ('suggest') and resource ('meeting slots') with a time constraint. However, it doesn't differentiate from sibling tools like 'create_event' or 'list_events' which handle different calendar operations, so it doesn't fully distinguish itself.

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. It doesn't mention sibling tools like 'create_event' for scheduling meetings or 'list_events' for viewing existing ones, nor does it specify prerequisites or contextual constraints for slot suggestion.

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

modify_emailC

Modify email labels (archive, trash, mark read/unread)

ParametersJSON Schema
NameRequiredDescriptionDefault
addLabelsNoLabels to add
idYesEmail ID
removeLabelsNoLabels to remove

TDQS

C2.9/5.0
Behavior2/5

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 implies a mutation operation ('Modify') but doesn't specify permissions required, whether changes are reversible, rate limits, or error conditions. The mention of actions like 'archive' and 'trash' hints at destructive behavior, but this isn't explicitly stated, leaving significant gaps.

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 a single, efficient sentence that front-loads the core purpose ('Modify email labels') and lists specific actions without unnecessary words. Every part earns its place, making it highly concise and well-structured.

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

Completeness2/5

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

Given the complexity of a mutation tool with no annotations and no output schema, the description is insufficient. It lacks details on behavioral traits (e.g., side effects, permissions), usage context, and expected outcomes, leaving the agent poorly equipped to handle this tool effectively in real-world scenarios.

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%, so the schema already documents all parameters (id, addLabels, removeLabels). The description adds minimal value by implying label types (e.g., 'archive', 'trash') but doesn't provide syntax details or examples beyond what the schema offers. 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.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Modify email labels') and specifies the types of modifications possible (archive, trash, mark read/unread), which distinguishes it from sibling tools like 'send_email' or 'list_emails'. However, it doesn't explicitly mention that it operates on existing emails or differentiate from potential label-specific tools, keeping it from 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.

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. It doesn't mention prerequisites (e.g., needing an email ID from 'list_emails' or 'search_emails'), exclusions, or comparisons to other tools like 'create_event' for related actions. This leaves the agent without context for tool selection.

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

search_emailsC

Search emails with advanced query

ParametersJSON Schema
NameRequiredDescriptionDefault
maxResultsNoMaximum number of emails to return (default: 10)
queryYesGmail search query (e.g., "from:example@gmail.com has:attachment")

TDQS

C2.9/5.0
Behavior2/5

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 mentions 'advanced query' but fails to detail key traits like whether this is a read-only operation, potential rate limits, authentication requirements, or what the output format entails. For a search tool with no 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.

Conciseness4/5

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

The description is a single, efficient sentence that gets straight to the point without unnecessary words. It's appropriately sized for a tool with two parameters, though it could be slightly more informative without sacrificing brevity. The structure is front-loaded but lacks elaboration.

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

Completeness2/5

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

Given the tool's complexity (search functionality with two parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't address behavioral aspects like safety, performance, or output format, leaving the agent with insufficient context for reliable use. This is inadequate for a search tool without structured support.

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 schema description coverage is 100%, with clear documentation for both parameters ('maxResults' and 'query'), including defaults and examples. The description adds no additional semantic meaning beyond the schema, such as explaining query syntax further or contextualizing parameter interactions. Baseline 3 is appropriate as the schema handles the heavy lifting.

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 clearly states the verb ('search') and resource ('emails'), making the purpose evident. However, it doesn't explicitly differentiate from sibling tools like 'list_emails' or 'modify_email', which might offer overlapping functionality. The 'advanced query' modifier adds some specificity but remains somewhat vague about what makes it 'advanced'.

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 like 'list_emails' or 'modify_email'. It lacks context about prerequisites, such as authentication needs or when advanced queries are preferable to simpler listing. This omission leaves the agent without clear usage boundaries.

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

send_emailC

Send a new email

ParametersJSON Schema
NameRequiredDescriptionDefault
bccNoBCC recipients (comma-separated)
bodyYesEmail body (can include HTML)
ccNoCC recipients (comma-separated)
subjectYesEmail subject
toYesRecipient email address

TDQS

C2.5/5.0
Behavior1/5

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. 'Send a new email' implies a write/mutation operation, but it doesn't disclose any behavioral traits such as permissions required, rate limits, whether it's synchronous/asynchronous, error handling, or what happens on success/failure. This is a significant gap for a mutation tool with zero annotation coverage.

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 with just three words, front-loaded with the core action. There's zero waste or redundancy, making it efficient for quick understanding, though this brevity contributes to gaps in other dimensions.

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

Completeness2/5

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

Given the complexity of sending an email (a mutation operation with potential side effects), no annotations, no output schema, and a minimal description, this is incomplete. The description doesn't address key contextual aspects like return values, error conditions, or integration with sibling tools, leaving the agent under-informed for safe and effective use.

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%, with all 5 parameters (to, subject, body, cc, bcc) well-documented in the input schema. The description adds no parameter semantics beyond what the schema provides, so it meets the baseline of 3 where the schema does the heavy lifting without compensating for any gaps.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Send a new email' clearly states the action (send) and resource (email), but it's quite basic and doesn't differentiate from potential sibling tools like 'modify_email' or provide any nuance about what constitutes a 'new' email versus other email operations. It avoids tautology but lacks specificity beyond the obvious.

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 like 'modify_email' or 'search_emails', nor does it mention any prerequisites or context for sending emails. It's a standalone statement with no usage context, leaving the agent to infer when this is appropriate.

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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TDQS

C2.6/5.0
Disambiguation2/5

The tool set mixes calendar and email operations without clear boundaries, causing potential misselection. For example, 'list_emails' and 'search_emails' overlap in purpose for email retrieval, while calendar tools like 'create_event' and 'list_events' are distinct but the server's dual-domain focus creates confusion.

Naming Consistency3/5

Naming conventions are mixed, with some tools using verb_noun patterns like 'create_event' and others using noun_verb like 'meeting_suggestion'. While readable, the inconsistency in structure (e.g., 'modify_email' vs. 'send_email') deviates from a predictable pattern.

Tool Count3/5

With 7 tools, the count is reasonable, but it feels borderline due to the server's split focus on both Google Calendar and Gmail. This scope might be too broad for the limited tool set, leading to a thin coverage in each domain.

Completeness2/5

For the implied dual-domain purpose, there are significant gaps. In calendar, tools lack update or delete event operations, and in email, there's no way to delete emails or manage drafts. The server name suggests calendar focus, but email tools are included without full lifecycle coverage.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

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