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al-one

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

企业微信应用号-发送文件消息

wework_app_send_file

Send files through WeChat Work application notifications to specified users or entire teams using file URLs.

Instructions

通过企业微信应用号发送发送文件消息

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes文件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 handler function for the 'wework_app_send_file' MCP tool. It defines the input schema using Pydantic Field for the file URL and target user, and executes by calling the shared wework_send_media helper with type 'file'.
    @mcp.tool(
        title="企业微信应用号-发送文件消息",
        description="通过企业微信应用号发送发送文件消息",
    )
    def wework_app_send_file(
        url: str = Field(description="文件URL"),
        touser: str = FIELD_TO_USER,
    ):
        return wework_send_media(touser, url, "file")
  • Helper function that implements the core logic for sending media (image, video, voice, file) via WeWork app: downloads from URL, determines type, uploads to media API using access token, then sends the media_id to the specified user.
    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()
  • Cached helper function to obtain the WeWork application access token, required for API calls like media upload and message sending.
    @cached(TTLCache(maxsize=1, ttl=3600))
    def get_access_token():
        res = requests.get(
            f"{WEWORK_BASE_URL}/cgi-bin/gettoken",
            params={"corpid": WEWORK_APP_CORPID, "corpsecret": WEWORK_APP_SECRET},
            timeout=60,
        )
        return res.json().get("access_token")
  • Calls add_tools from the wework module to register all WeWork-related tools, including 'wework_app_send_file', onto the FastMCP instance.
    wework.add_tools(mcp)
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It states the tool sends file messages but doesn't disclose behavioral traits such as authentication requirements, rate limits, error handling, or what happens on success/failure. For a messaging tool with zero annotation coverage, this leaves significant gaps in understanding how it operates.

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 that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, with every part contributing to understanding the core function.

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 the tool's moderate complexity (sending files via an API), lack of annotations, and no output schema, the description is minimally adequate. It covers the basic purpose but misses important context like authentication, response format, or error conditions. With no structured fields to rely on, the description should do more to be complete.

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%, with both parameters ('url' and 'touser') well-documented in the schema. The description adds no additional parameter information beyond what's in the schema. According to the rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.

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 ('发送文件消息' - send file message) and the target resource ('企业微信应用号' - WeChat Work application). It distinguishes from siblings like 'wework_app_send_text' or 'wework_app_send_image' by specifying file messages. However, it doesn't explicitly contrast with 'tg_send_file' or other file-sending tools, which would be needed for a perfect score.

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. It doesn't mention when to choose file messages over text, image, or other media types in the WeChat Work context, nor does it reference sibling tools like 'wework_app_send_text' or 'tg_send_file'. Usage is implied by the tool name but not explicitly stated.

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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