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zapcap_mcp_upload_video_by_url

Upload video files to ZapCap by providing a URL. This tool processes video uploads through the ZapCap API for subsequent tasks.

Instructions

Upload video by URL to ZapCap

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
requestYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The handler function that implements the zapcap_mcp_upload_video_by_url tool. It sends a POST request to the ZapCap API with the provided URL to upload the video.
    def zapcap_mcp_upload_video_by_url(request: UploadVideoByUrl) -> Dict[str, Any]:
        headers = {
            "x-api-key": get_api_key(),
            "Content-Type": "application/json"
        }
        
        data = {"url": request.url}
        with httpx.Client() as client:
            response = client.post(
                "https://api.zapcap.ai/videos/url",
                headers=headers,
                json=data
            )
        
        response.raise_for_status()
        return response.json()
  • Pydantic BaseModel defining the input schema for the tool, which requires a 'url' field.
    class UploadVideoByUrl(BaseModel):
        url: str = Field(description="URL to video file")
  • The @mcp.tool decorator that registers the function as an MCP tool with its description.
    @mcp.tool(description="Upload video by URL to ZapCap")
  • Helper function to retrieve the ZapCap API key from environment variable, used in the tool handler.
    def get_api_key() -> str:
        api_key = os.getenv("ZAPCAP_API_KEY")
        if not api_key:
            raise ValueError("ZAPCAP_API_KEY environment variable is required")
        return api_key
Behavior1/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure but fails to do so. It doesn't indicate whether this is a read-only or destructive operation, what permissions are required, if there are rate limits, or what the expected outcome is (e.g., success/failure response, video processing). For a mutation tool ('Upload'), this lack of transparency is a critical gap.

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 wasted words, front-loading the core action ('Upload video by URL'). It's appropriately sized for a simple tool, 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 the tool's complexity (a mutation operation with no annotations) and the presence of an output schema, the description is incomplete. It doesn't address behavioral aspects like side effects, authentication needs, or error handling, which are crucial for safe invocation. While the output schema may cover return values, the description fails to provide enough context for the agent to understand the tool's full implications.

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?

The description implies a 'url' parameter but doesn't add any semantic details beyond what the input schema provides. With 0% schema description coverage, the schema only documents the parameter name and type, and the description doesn't compensate by explaining URL formats, supported protocols, or validation rules. However, since there's only one parameter, the baseline is 4, but the lack of added value reduces it to 3.

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 'Upload video by URL to ZapCap' clearly states the verb ('Upload'), resource ('video'), and mechanism ('by URL'), making the purpose immediately understandable. It distinguishes from the sibling 'zapcap_mcp_upload_video' by specifying the URL-based approach, though it doesn't explicitly contrast them. However, it lacks specificity about what ZapCap is or what happens after upload, keeping it from 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 like 'zapcap_mcp_upload_video' or other siblings. It doesn't mention prerequisites, constraints, or typical scenarios for URL-based uploads, leaving the agent to infer usage from the name alone. This minimal guidance is insufficient for informed tool 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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