Skip to main content
Glama

list_threads

Retrieve email conversation threads from a Gmail mailbox with filtering options for search queries, labels, and result limits.

Instructions

List threads in the user's mailbox

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
maxResultsNoMaximum number of threads to return
pageTokenNoPage token to retrieve a specific page of results
qNoOnly return threads matching the specified query
labelIdsNoOnly return threads with labels that match all of the specified label IDs
includeSpamTrashNoInclude threads from SPAM and TRASH in the results
includeBodyHtmlNoWhether to include the parsed HTML in the return for each body, excluded by default because they can be excessively large

Implementation Reference

  • Full implementation of the 'list_threads' tool, including registration, input schema, and handler function. The handler calls the Gmail API to list threads, optionally decodes and processes message payloads (filtering headers, decoding base64 bodies), and formats the response.
    server.tool("list_threads",
      "List threads in the user's mailbox",
      {
        maxResults: z.number().optional().describe("Maximum number of threads to return"),
        pageToken: z.string().optional().describe("Page token to retrieve a specific page of results"),
        q: z.string().optional().describe("Only return threads matching the specified query"),
        labelIds: z.array(z.string()).optional().describe("Only return threads with labels that match all of the specified label IDs"),
        includeSpamTrash: z.boolean().optional().describe("Include threads from SPAM and TRASH in the results"),
        includeBodyHtml: z.boolean().optional().describe("Whether to include the parsed HTML in the return for each body, excluded by default because they can be excessively large"),
      },
      async (params) => {
        return handleTool(config, async (gmail: gmail_v1.Gmail) => {
          const { data } = await gmail.users.threads.list({ userId: 'me', ...params })
    
          if (data.threads) {
            data.threads = data.threads.map(thread => {
              if (thread.messages) {
                thread.messages = thread.messages.map(message => {
                  if (message.payload) {
                    message.payload = processMessagePart(
                      message.payload,
                      params.includeBodyHtml
                    )
                  }
                  return message
                })
              }
              return thread
            })
          }
    
          return formatResponse(data)
        })
      }
    )
  • Input schema (Zod) for the list_threads tool parameters.
    {
      maxResults: z.number().optional().describe("Maximum number of threads to return"),
      pageToken: z.string().optional().describe("Page token to retrieve a specific page of results"),
      q: z.string().optional().describe("Only return threads matching the specified query"),
      labelIds: z.array(z.string()).optional().describe("Only return threads with labels that match all of the specified label IDs"),
      includeSpamTrash: z.boolean().optional().describe("Include threads from SPAM and TRASH in the results"),
      includeBodyHtml: z.boolean().optional().describe("Whether to include the parsed HTML in the return for each body, excluded by default because they can be excessively large"),
    },
  • Helper function used by list_threads to recursively process message parts: decode base64 bodies (unless HTML and not requested), filter headers to specific list, used to clean up responses.
    const processMessagePart = (messagePart: MessagePart, includeBodyHtml = false): MessagePart => {
      if ((messagePart.mimeType !== 'text/html' || includeBodyHtml) && messagePart.body) {
        messagePart.body = decodedBody(messagePart.body)
      }
    
      if (messagePart.parts) {
        messagePart.parts = messagePart.parts.map(part => processMessagePart(part, includeBodyHtml))
      }
    
      if (messagePart.headers) {
        messagePart.headers = messagePart.headers.filter(header => RESPONSE_HEADERS_LIST.includes(header.name || ''))
      }
    
      return messagePart
    }
  • Shared helper invoked by list_threads handler: handles OAuth2 client creation/validation, Gmail client setup, executes the API call, catches errors.
    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) {
        return `Tool execution failed: ${error.message}`
      }
    }
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 but only states the basic action. It does not cover critical aspects like pagination behavior, rate limits, authentication needs, or what the return format looks like, leaving significant gaps for an agent.

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 with no wasted words, making it easy to parse and front-loaded with the essential action. It efficiently communicates the core purpose without unnecessary 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 lack of annotations and output schema, the description is insufficient for a tool with six parameters and complex filtering options. It fails to explain return values, error conditions, or behavioral nuances, leaving the agent with incomplete context for 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?

The input schema has 100% description coverage, fully documenting all six parameters. The description adds no additional semantic details beyond what the schema provides, such as examples or usage tips, meeting the baseline for adequate but not enhanced parameter understanding.

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 ('threads in the user's mailbox'), making the purpose evident. However, it does not differentiate from sibling tools like 'list_messages' or 'list_drafts', which are similar listing operations, leaving room for ambiguity in tool selection.

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 such as 'list_messages' or 'get_thread'. The description lacks context about prerequisites, exclusions, or specific use cases, offering minimal assistance in decision-making.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/HitmanLy007/gmail-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server