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uraoz

Bouyomi-chan MCP Server

by uraoz

read_text

Convert text to speech using Bouyomi-chan's TTS functionality via Model Context Protocol (MCP). Ideal for AI assistants to voice-read text with customizable parameters for enhanced interaction.

Instructions

テキストを棒読みちゃんで読み上げます

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Handler function that executes the read_text tool: sends text to BouyomiChan API via speakBouyomi helper and returns success or error response.
    async ({ text, voice = 0, volume = -1, speed = -1, tone = -1 }) => {
      const statusCode = await speakBouyomi(text, voice, volume, speed, tone);
      
      if (statusCode === 200) {
        return {
          content: [
            {
              type: "text",
              text: `読み上げました`
            }
          ]
        };
      } else {
        return {
          content: [
            {
              type: "text",
              text: `読み上げに失敗しました。ステータスコード: ${statusCode}`
            }
          ],
          isError: true
        };
      }
    }
  • Zod schema defining input parameters for the read_text tool.
    {
      text: z.string().describe("読み上げるテキスト"),
      voice: z.number().default(0).describe("音声の種類(0: 女性1、1: 男性1、2: 女性2、...)"),
      volume: z.number().default(-1).describe("音量(-1: デフォルト、0-100: 音量レベル)"),
      speed: z.number().default(-1).describe("速度(-1: デフォルト、50-200: 速度レベル)"),
      tone: z.number().default(-1).describe("音程(-1: デフォルト、50-200: 音程レベル)")
    },
  • src/index.ts:42-76 (registration)
    Registration of the read_text tool on the MCP server using server.tool().
    server.tool(
      "read_text",
      "テキストを棒読みちゃんで読み上げます",
      {
        text: z.string().describe("読み上げるテキスト"),
        voice: z.number().default(0).describe("音声の種類(0: 女性1、1: 男性1、2: 女性2、...)"),
        volume: z.number().default(-1).describe("音量(-1: デフォルト、0-100: 音量レベル)"),
        speed: z.number().default(-1).describe("速度(-1: デフォルト、50-200: 速度レベル)"),
        tone: z.number().default(-1).describe("音程(-1: デフォルト、50-200: 音程レベル)")
      },
      async ({ text, voice = 0, volume = -1, speed = -1, tone = -1 }) => {
        const statusCode = await speakBouyomi(text, voice, volume, speed, tone);
        
        if (statusCode === 200) {
          return {
            content: [
              {
                type: "text",
                text: `読み上げました`
              }
            ]
          };
        } else {
          return {
            content: [
              {
                type: "text",
                text: `読み上げに失敗しました。ステータスコード: ${statusCode}`
              }
            ],
            isError: true
          };
        }
      }
    );
  • Helper function that sends HTTP request to BouyomiChan server to speak the text.
    async function speakBouyomi(
      text: string = 'ゆっくりしていってね',
      voice: number = 0,
      volume: number = -1,
      speed: number = -1,
      tone: number = -1
    ): Promise<number> {
      try {
        const response = await axios.get('http://localhost:50080/Talk', {
          params: {
            text,
            voice,
            volume,
            speed,
            tone
          }
        });
        return response.status;
      } catch (error) {
        console.error('棒読みちゃんへのリクエストに失敗しました:', error);
        return 500;
      }
    }
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 mentions the reading happens 'with a monotone voice' which is useful behavioral context, but doesn't disclose other important traits: whether this is a synchronous or asynchronous operation, what happens with long texts, error conditions, or what the output actually is (audio file, playback, etc.). For a tool with zero annotation coverage, this is insufficient.

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 Japanese sentence that directly states what the tool does. Every word earns its place: 'テキスト' (text), '棒読みちゃん' (monotone voice), '読み上げます' (reads aloud). No wasted words or 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 tool has no annotations, no output schema, and zero parameters, the description should provide more complete context. While it states the basic purpose, it doesn't explain what form the output takes (audio stream, file, immediate playback), performance limitations, or error handling. For a text-to-speech tool, this leaves significant gaps in understanding how to use it effectively.

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 zero parameters, and schema description coverage is 100%. The description doesn't need to explain parameters, and it correctly implies text input through its purpose statement. Baseline for zero parameters with full schema coverage is 4, as there's nothing to compensate for.

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: 'テキストを棒読みちゃんで読み上げます' translates to 'Reads text aloud with a monotone voice'. This specifies the verb ('reads aloud') and resource ('text'), though it doesn't need to distinguish from siblings since none exist. The mention of 'monotone voice' adds specificity about the reading style.

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, context for usage, or any exclusions. While no sibling tools exist to differentiate from, it lacks basic usage context like input format expectations or performance characteristics.

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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