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al-one

MCP Server for notify to weixin / telegram / bark / lark

Telegram send audio

tg_send_audio

Send audio files through Telegram bots to share voice messages, podcasts, or recordings with specified chats using URLs and optional captions.

Instructions

Send audio via telegram bot

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
audioYesAudio URL
chat_idNoTelegram chat id, Default to get from environment variables
captionNoAudio caption, 0-1024 characters after entities parsing
parse_modeNoMode for parsing entities in the caption. [text/MarkdownV2]
reply_to_message_idNoIdentifier of the message that will be replied to

Implementation Reference

  • The asynchronous handler function that implements the logic to send an audio file via the Telegram Bot API.
    async def tg_send_audio(
        audio: str = Field(description="Audio URL"),
        chat_id: str = Field("", description="Telegram chat id, Default to get from environment variables"),
        caption: str = Field("", description="Audio caption, 0-1024 characters after entities parsing"),
        parse_mode: str = Field("", description=f"Mode for parsing entities in the caption. [text/MarkdownV2]"),
        reply_to_message_id: int = Field(0, description="Identifier of the message that will be replied to"),
    ):
        if parse_mode == TELEGRAM_MARKDOWN_V2:
            caption = telegramify_markdown.markdownify(caption)
        res = await bot.send_audio(
            chat_id=chat_id or TELEGRAM_DEFAULT_CHAT,
            audio=audio,
            caption=caption or None,
            parse_mode=parse_mode if parse_mode in [TELEGRAM_MARKDOWN_V2] else None,
            reply_to_message_id=reply_to_message_id or None,
        )
        return res.to_json()
  • The @mcp.tool decorator that registers the tg_send_audio tool with the FastMCP instance.
    @mcp.tool(
        title="Telegram send audio",
        description="Send audio via telegram bot",
    )
  • Invocation of tgbot.add_tools(mcp) which triggers the registration of Telegram tools, including tg_send_audio.
    tgbot.add_tools(mcp)
  • Pydantic Field definitions providing input schema, descriptions, and defaults for the tg_send_audio tool parameters.
    audio: str = Field(description="Audio URL"),
    chat_id: str = Field("", description="Telegram chat id, Default to get from environment variables"),
    caption: str = Field("", description="Audio caption, 0-1024 characters after entities parsing"),
    parse_mode: str = Field("", description=f"Mode for parsing entities in the caption. [text/MarkdownV2]"),
    reply_to_message_id: int = Field(0, description="Identifier of the message that will be replied to"),
  • Creation of the shared Telegram Bot instance used by tg_send_audio and other Telegram tools.
    bot = Bot(
        TELEGRAM_BOT_TOKEN,
        base_url=f"{TELEGRAM_BASE_URL}/bot",
        base_file_url=f"{TELEGRAM_BASE_URL}/file/bot",
    ) if TELEGRAM_BOT_TOKEN else None
Behavior2/5

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

With no annotations provided, the description carries full burden but offers minimal behavioral insight. It mentions sending audio but doesn't disclose permissions needed, rate limits, error conditions, or what happens on success (e.g., message ID returned). This is inadequate 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 a single, efficient sentence with zero wasted words. It is front-loaded with the core action and resource, making it highly concise and well-structured for quick comprehension.

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 lacks details on behavioral traits, error handling, return values, and usage context, leaving significant gaps in understanding how to effectively invoke this tool.

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 fully documents all 5 parameters. The description adds no parameter-specific information beyond what's in the schema, maintaining the baseline score of 3 where 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 action ('send') and resource ('audio via telegram bot'), making the purpose immediately understandable. It distinguishes from siblings like tg_send_message or tg_send_file by specifying the media type, though it doesn't explicitly contrast with them.

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 tg_send_message for text or tg_send_file for generic files. The description lacks context about appropriate scenarios or prerequisites, leaving usage decisions entirely to the agent's inference.

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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