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list_labels

Retrieve all Gmail labels from your mailbox to organize and categorize emails effectively.

Instructions

List all labels in the user's mailbox

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • src/index.ts:481-490 (registration)
    Registration of the 'list_labels' tool. Includes empty input schema and inline handler function that uses the shared 'handleTool' helper to call Gmail API's users.labels.list and format the response.
    server.tool("list_labels",
      "List all labels in the user's mailbox",
      {},
      async () => {
        return handleTool(config, async (gmail: gmail_v1.Gmail) => {
          const { data } = await gmail.users.labels.list({ userId: 'me' })
          return formatResponse(data)
        })
      }
    )
  • Inline handler function for 'list_labels' tool, which authenticates via handleTool, lists labels using Gmail API, and formats the response.
    async () => {
      return handleTool(config, async (gmail: gmail_v1.Gmail) => {
        const { data } = await gmail.users.labels.list({ userId: 'me' })
        return formatResponse(data)
      })
    }
  • Input schema for 'list_labels' tool: no parameters required.
    {},
  • Shared 'handleTool' helper used by 'list_labels' and other tools for authentication, Gmail client creation, API call execution, and error handling.
    const handleTool = async (queryConfig: Record<string, any> | undefined, apiCall: (gmail: gmail_v1.Gmail) => Promise<any>) => {
      try {
        const oauth2Client = queryConfig ? createOAuth2Client(queryConfig) : defaultOAuth2Client
        if (!oauth2Client) throw new Error('OAuth2 client could not be created, please check your credentials')
    
        const credentialsAreValid = await validateCredentials(oauth2Client)
        if (!credentialsAreValid) throw new Error('OAuth2 credentials are invalid, please re-authenticate')
    
        const gmailClient = queryConfig ? google.gmail({ version: 'v1', auth: oauth2Client }) : defaultGmailClient
        if (!gmailClient) throw new Error('Gmail client could not be created, please check your credentials')
    
        const result = await apiCall(gmailClient)
        return result
      } catch (error: any) {
        // Check for specific authentication errors
        if (
          error.message?.includes("invalid_grant") ||
          error.message?.includes("refresh_token") ||
          error.message?.includes("invalid_client") ||
          error.message?.includes("unauthorized_client") ||
          error.code === 401 ||
          error.code === 403
        ) {
          return formatResponse({
            error: `Authentication failed: ${error.message}. Please re-authenticate by running: npx @shinzolabs/gmail-mcp auth`,
          });
        }
    
        return formatResponse({ error: `Tool execution failed: ${error.message}` });
      }
    }
  • Shared 'formatResponse' helper used to wrap tool responses in MCP format.
    const formatResponse = (response: any) => ({ content: [{ type: "text", text: JSON.stringify(response) }] })
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 states the action but doesn't cover important aspects like whether this is a read-only operation, if it requires authentication, how results are returned (e.g., pagination, format), or any rate limits. The description is too minimal for a tool with behavioral implications.

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, clear sentence that efficiently communicates the core functionality without any wasted words. It's appropriately sized and front-loaded with 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?

Given the tool has no annotations and no output schema, the description is insufficiently complete. It doesn't explain what the return values look like (e.g., list format, label properties included) or address behavioral aspects like authentication requirements or error conditions. For a list operation that likely returns structured data, more context is needed.

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

Parameters4/5

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

The tool has 0 parameters with 100% schema description coverage, so no parameter documentation is needed. The description appropriately doesn't mention parameters, which is correct for this case. A baseline of 4 is appropriate since the schema fully covers the parameter aspect.

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 ('List') and resource ('all labels in the user's mailbox'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_label' (which fetches a specific label) or 'create_label' (which creates new labels), missing full sibling 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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to prefer 'list_labels' over 'get_label' for retrieving a single label, or when to use it in conjunction with operations like 'create_label' or 'delete_label'.

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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