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

by aahl

企业微信应用号-发送图片消息

wework_app_send_image

Send an image message to WeChat Work users by providing a URL. Optionally specify target users or use @all to notify everyone.

Instructions

通过企业微信应用号发送发送图片消息

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes图片URL
touserNo接收消息的成员ID,多个用`|`分隔,为`@all`时向该企业应用全部成员发送,默认从环境变量获取

Implementation Reference

  • The 'wework_app_send_image' tool handler function. It downloads an image from a URL and delegates to 'wework_send_media' with msgtype='image'. Registered as an MCP tool via @mcp.tool decorator.
    def wework_app_send_image(
        url: str = Field(description="图片URL"),
        touser: str = FIELD_TO_USER,
    ):
        return wework_send_media(touser, url, "image")
  • The 'wework_send_media' helper function called by 'wework_app_send_image'. Downloads media from a URL, uploads it to WeWork's media API, then sends it as an application message with the returned media_id.
    def wework_send_media(touser, url: str, msgtype=None):
        if msgtype:
            pass
        elif '.jpg' in url.lower() or '.jpeg' in url.lower() or '.png' in url.lower():
            msgtype = 'image'
        elif '.mp4' in url.lower():
            msgtype = 'video'
        elif '.arm' in url.lower():
            msgtype = 'voice'
        else:
            msgtype = 'file'
        res = requests.get(url, timeout=120)
        res.raise_for_status()
        file = io.BytesIO(res.content)
        mine = res.headers.get("content-type") or "application/octet-stream"
        res = requests.post(
            f"{WEWORK_BASE_URL}/cgi-bin/media/upload",
            params={"type": msgtype, "access_token": get_access_token()},
            files={"media": ("filename", file, mine)},
            timeout=120,
        )
        media = res.json() or {}
        if not (media_id := media.get("media_id")):
            return media
        res = requests.post(
            f"{WEWORK_BASE_URL}/cgi-bin/message/send?access_token={get_access_token()}",
            json={
                "touser": touser or WEWORK_APP_TOUSER,
                "agentid": WEWORK_APP_AGENTID,
                "msgtype": msgtype,
                msgtype: {"media_id": media_id},
            },
        )
        return res.json()
  • Registration point: 'wework.add_tools(mcp)' is called, which registers all WeWork tools including 'wework_app_send_image' via the @mcp.tool decorator inside the add_tools function.
    mcp = FastMCP(name="mcp-notify", version="0.1.11")
    wework.add_tools(mcp)
    tgbot.add_tools(mcp)
    other.add_tools(mcp)
    hass.add_tools(mcp)
    util.add_tools(mcp)
  • Schema definition: The 'FIELD_TO_USER' constant is used as a default value for the 'touser' parameter in 'wework_app_send_image', defining its input schema.
    FIELD_BOT_KEY = Field("", description="企业微信群机器人key,uuid格式,默认从环境变量获取")
    FIELD_TO_USER = Field("", description="接收消息的成员ID,多个用`|`分隔,为`@all`时向该企业应用全部成员发送,默认从环境变量获取")

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.5/5.0
Behavior2/5

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

With no annotations, the description carries the full burden. It only says '发送图片消息' but does not disclose any behavioral traits like image format requirements, size limits, or whether the operation is destructive. This is insufficient for an agent to understand the tool's behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very short (one line) but contains a typo (duplicate '发送'). While concise, the typo reduces clarity. It is not front-loaded with key information.

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 2 parameters, no output schema, and no annotations, the description is minimal. It does not explain return values, error conditions, or the effect of the 'touser' parameter default behavior. Incomplete for practical use.

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 both parameters. The description adds no additional meaning beyond the schema. Baseline 3 is appropriate as the description does not enhance parameter understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states '通过企业微信应用号发送发送图片消息' which indicates sending image messages via WeChat Work application. However, the duplicate '发送' and lack of distinction from siblings like 'wework_send_image' or 'wework_app_send_file' make it vague. The purpose is clear but not specific enough to differentiate.

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 on when to use this tool versus alternatives such as 'wework_send_image' or other messaging tools. No context about when it is appropriate or when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.