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Angad-2002

Attendee MCP Server

by Angad-2002

make_bot_speak

Convert text to speech for a bot to speak during meetings, supporting multiple languages and voice options for clear audio output.

Instructions

Make a bot speak text during a meeting using text-to-speech

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bot_idYesID of the bot that should speak
textYesText for the bot to speak
voice_language_codeNoVoice language code (optional, defaults to 'en-US')en-US
voice_nameNoVoice name (optional, defaults to 'en-US-Casual-K')en-US-Casual-K

Implementation Reference

  • The main handler function for the 'make_bot_speak' tool. It validates inputs, constructs TTS settings, sends a POST request to the API endpoint `/api/v1/bots/{bot_id}/speech`, and returns a success message.
    private async makeBotSpeak(args: Record<string, unknown>) {
      const bot_id = args.bot_id as string;
      const text = args.text as string;
      const voice_language_code = (args.voice_language_code as string) || "en-US";
      const voice_name = (args.voice_name as string) || "en-US-Casual-K";
      
      if (!bot_id || typeof bot_id !== 'string') {
        throw new Error("Missing or invalid required parameter: bot_id");
      }
      
      if (!text || typeof text !== 'string') {
        throw new Error("Missing or invalid required parameter: text");
      }
      
      const speechData = {
        text,
        text_to_speech_settings: {
          google: {
            voice_language_code,
            voice_name
          }
        }
      };
    
      await this.makeApiRequest(`/api/v1/bots/${bot_id}/speech`, "POST", speechData);
    
      return {
        content: [
          {
            type: "text",
            text: `āœ… Bot ${bot_id} will speak: "${text}"\n\nšŸ”Š Voice: ${voice_name} (${voice_language_code})\nšŸ’” The bot should now be speaking in the meeting!`,
          },
        ],
      };
    }
  • The input schema definition for the 'make_bot_speak' tool, specifying parameters like bot_id (required), text (required), voice_language_code, and voice_name with types, descriptions, and defaults.
    inputSchema: {
      type: "object",
      properties: {
        bot_id: {
          type: "string",
          description: "ID of the bot that should speak",
        },
        text: {
          type: "string",
          description: "Text for the bot to speak",
        },
        voice_language_code: {
          type: "string",
          description: "Voice language code (optional, defaults to 'en-US')",
          default: "en-US",
        },
        voice_name: {
          type: "string",
          description: "Voice name (optional, defaults to 'en-US-Casual-K')",
          default: "en-US-Casual-K",
        },
      },
      required: ["bot_id", "text"],
    },
  • src/index.ts:422-423 (registration)
    Registration in the switch statement of the CallToolRequestHandler that dispatches calls to 'make_bot_speak' to the makeBotSpeak handler method.
    case "make_bot_speak":
      return await this.makeBotSpeak(args);
  • src/index.ts:275-302 (registration)
    Tool registration in the ListToolsRequestHandler response, including name, description, and full input schema.
    {
      name: "make_bot_speak",
      description: "Make a bot speak text during a meeting using text-to-speech",
      inputSchema: {
        type: "object",
        properties: {
          bot_id: {
            type: "string",
            description: "ID of the bot that should speak",
          },
          text: {
            type: "string",
            description: "Text for the bot to speak",
          },
          voice_language_code: {
            type: "string",
            description: "Voice language code (optional, defaults to 'en-US')",
            default: "en-US",
          },
          voice_name: {
            type: "string",
            description: "Voice name (optional, defaults to 'en-US-Casual-K')",
            default: "en-US-Casual-K",
          },
        },
        required: ["bot_id", "text"],
      },
    },
Behavior2/5

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

No annotations are provided, so the description carries full burden. It states the action but doesn't disclose behavioral traits: it doesn't mention if this requires specific permissions, whether it interrupts ongoing speech, rate limits, error conditions (e.g., invalid bot_id), or what happens on success/failure. For a mutation tool with zero annotation coverage, this is a significant gap.

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 ('make a bot speak text during a meeting') and adds mechanism ('using text-to-speech'). Every word earns its place with zero waste or redundancy.

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 complexity (mutation tool with 4 parameters), no annotations, and no output schema, the description is incomplete. It lacks behavioral details (e.g., permissions, effects), usage context, and output information. For a tool that modifies meeting state, this leaves significant gaps for an AI agent.

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 4 parameters with descriptions. The description adds no additional meaning beyond implying 'text' is spoken and 'bot_id' identifies the bot, which is redundant with schema info. Baseline is 3 since schema does the heavy lifting, but no extra value is added.

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 ('make a bot speak') and the mechanism ('using text-to-speech'), specifying both verb and resource. It distinguishes from siblings like 'send_chat_message' or 'send_image_to_meeting' by focusing on speech output rather than text/visual communication. However, it doesn't explicitly differentiate from all siblings (e.g., 'get_bot_status' is clearly different, but the distinction could be more explicit).

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., bot must be active in a meeting), exclusions (e.g., not for text display), or comparisons to siblings like 'send_chat_message' for text-based communication. Usage is implied by the action but lacks explicit context.

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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