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al-one

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

Telegram send text

tg_send_message

Send text or markdown messages via Telegram bot for notifications across multiple platforms including Weixin, Bark, and Lark.

Instructions

Send text or markdown message via telegram bot

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesText of the message to be sent, 1-4096 characters after entities parsing
chat_idNoTelegram chat id, Default to get from environment variables
parse_modeNoMode for parsing entities in the message text. [text/MarkdownV2]
reply_to_message_idNoIdentifier of the message that will be replied to

Implementation Reference

  • The handler function for the 'tg_send_message' tool. It sends a text message via Telegram bot, handling MarkdownV2 parsing if specified, and returns the JSON response.
    @mcp.tool(
        title="Telegram send text",
        description="Send text or markdown message via telegram bot",
    )
    async def tg_send_message(
        text: str = Field(description="Text of the message to be sent, 1-4096 characters after entities parsing"),
        chat_id: str = Field("", description="Telegram chat id, Default to get from environment variables"),
        parse_mode: str = Field("", description=f"Mode for parsing entities in the message text. [text/MarkdownV2]"),
        reply_to_message_id: int = Field(0, description="Identifier of the message that will be replied to"),
    ):
        if not bot:
            return "Please set the `TELEGRAM_BOT_TOKEN` environment variable"
        if parse_mode == TELEGRAM_MARKDOWN_V2:
            text = telegramify_markdown.markdownify(text)
        res = await bot.send_message(
            chat_id=chat_id or TELEGRAM_DEFAULT_CHAT,
            text=text,
            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()
  • Registers all Telegram bot tools, including 'tg_send_message', by calling the add_tools function from tgbot module on the FastMCP instance.
    tgbot.add_tools(mcp)
  • Creates the Telegram Bot instance used by the tg_send_message 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
  • Pydantic Field definitions providing input schema and descriptions for the tg_send_message tool parameters.
        text: str = Field(description="Text of the message to be sent, 1-4096 characters after entities parsing"),
        chat_id: str = Field("", description="Telegram chat id, Default to get from environment variables"),
        parse_mode: str = Field("", description=f"Mode for parsing entities in the message text. [text/MarkdownV2]"),
        reply_to_message_id: int = Field(0, description="Identifier of the message that will be replied to"),
    ):
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. While 'Send' implies a write operation, it doesn't mention authentication requirements (bot token), rate limits, error conditions, or what happens on success/failure. For a messaging tool with zero annotation coverage, this leaves significant behavioral gaps.

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 extremely concise - a single sentence that states the core functionality without any wasted words. It's front-loaded with the essential information and earns its place efficiently.

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 messaging tool with no annotations and no output schema, the description is insufficiently complete. It doesn't address authentication, error handling, success responses, or platform-specific considerations. Given the complexity of messaging operations and the lack of structured metadata, more context is needed.

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 parameters thoroughly. The description adds no additional parameter information beyond what's in the schema, maintaining the baseline score. It doesn't explain relationships between parameters or provide usage examples.

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 ('text or markdown message via telegram bot'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like tg_send_audio or tg_send_photo, which would require mentioning this is specifically for text/markdown messages.

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. With multiple sibling tools for different message types (audio, file, photo, video) and other platforms (bark, ding, lark, etc.), there's no indication of when this Telegram text tool is appropriate versus other messaging options.

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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