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al-one

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

Telegram send video

tg_send_video

Send video notifications through Telegram bots by providing a video URL, optional caption, and chat ID. This tool enables automated video sharing within the MCP notification server.

Instructions

Send video via telegram bot

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
videoYesVideo URL
coverNoCover for the video in the message. Optional
chat_idNoTelegram chat id, Default to get from environment variables
captionNoVideo 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 core handler function for the 'tg_send_video' tool. It processes the input parameters, handles MarkdownV2 parsing for captions if specified, and uses the Telegram Bot API's send_video method to send the video to the specified chat.
    async def tg_send_video(
        video: str = Field(description="Video URL"),
        cover: str = Field("", description="Cover for the video in the message. Optional"),
        chat_id: str = Field("", description="Telegram chat id, Default to get from environment variables"),
        caption: str = Field("", description="Video 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_video(
            chat_id=chat_id or TELEGRAM_DEFAULT_CHAT,
            video=video,
            cover=cover or None,
            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_video', by calling add_tools on the FastMCP instance.
    tgbot.add_tools(mcp)
  • Pydantic Field definitions providing input schema validation and descriptions for the tg_send_video tool parameters.
        video: str = Field(description="Video URL"),
        cover: str = Field("", description="Cover for the video in the message. Optional"),
        chat_id: str = Field("", description="Telegram chat id, Default to get from environment variables"),
        caption: str = Field("", description="Video 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"),
    ):
  • The @mcp.tool decorator registers the tg_send_video function as an MCP tool with its title and description.
    @mcp.tool(
        title="Telegram send video",
        description="Send video via telegram bot",
    )
  • Initializes the shared Telegram Bot instance used by tg_send_video and other tg_send_* tools, reading configuration from environment variables.
    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 only states the basic action without disclosing behavioral traits. It doesn't cover aspects like authentication needs (e.g., bot token requirements), rate limits, error handling, or what happens on success/failure, which are critical for a mutation tool like sending video.

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 waste. It's front-loaded and appropriately sized for its purpose, making it easy to parse quickly without 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 this is a mutation tool with no annotations and no output schema, the description is incomplete. It lacks critical context like authentication requirements, response format, error conditions, or how it integrates with the Telegram bot API, leaving significant gaps for an agent to use it effectively.

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 6 parameters. The description adds no additional meaning beyond the schema, such as explaining parameter interactions or usage nuances. Baseline 3 is appropriate as the schema handles 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 'Send video via telegram bot' clearly states the action (send) and resource (video) with the platform context (telegram bot). It distinguishes from siblings like tg_send_audio or tg_send_photo by specifying video, though it doesn't explicitly contrast with other Telegram tools beyond the resource type.

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. It doesn't mention when to choose video over other media types like audio or photo, or how it differs from general messaging tools like tg_send_message, leaving usage context implied at best.

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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