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al-one

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

Telegram send file

tg_send_file

Send files to Telegram chats using a bot by providing a URL, with options for captions, reply threading, and chat targeting.

Instructions

Send general files via telegram bot

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesFile URL
chat_idNoTelegram chat id, Default to get from environment variables
captionNoFile 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 handler function for tg_send_file tool. It uses the Telegram Bot to send a document (file) from a URL, with optional caption, parse_mode, and reply_to. The input parameters are defined with Pydantic Fields, serving as the schema. MarkdownV2 captions are processed with telegramify_markdown. The function is registered via @mcp.tool decorator.
    @mcp.tool(
        title="Telegram send file",
        description="Send general files via telegram bot",
    )
    async def tg_send_file(
        url: str = Field(description="File URL"),
        chat_id: str = Field("", description="Telegram chat id, Default to get from environment variables"),
        caption: str = Field("", description="File 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_document(
            chat_id=chat_id or TELEGRAM_DEFAULT_CHAT,
            document=url,
            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()
  • Registers all tools from the tgbot module, including tg_send_file, by calling its add_tools function on the FastMCP instance.
    tgbot.add_tools(mcp)
  • Imports the tgbot module which contains the tg_send_file tool implementation.
    from . import (
        wework,
        tgbot,
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 but offers minimal behavioral insight. It mentions sending files but doesn't disclose authentication needs, rate limits, error handling, or what happens on success/failure. For a tool with no annotations, this leaves significant gaps in understanding its operation.

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 no wasted words. It's appropriately sized and front-loaded, clearly stating the tool's purpose without unnecessary elaboration.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 5 parameters with full schema coverage but no annotations or output schema, the description is minimally adequate. It states the basic purpose but lacks behavioral details, usage context, and output information, making it incomplete for optimal agent use despite the good schema support.

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 additional parameter semantics beyond what's in the schema, such as explaining the relationship between parameters or usage nuances. Baseline 3 is appropriate when schema handles documentation.

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 ('general files via telegram bot'), making the purpose understandable. However, it doesn't differentiate from sibling tools like tg_send_audio, tg_send_photo, or tg_send_video, which are all file/media sending tools for Telegram.

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. The description doesn't mention when to choose tg_send_file over tg_send_audio, tg_send_photo, or tg_send_video, or any other sibling tools, leaving the agent without context for selection.

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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