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mcp-metricool

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by metricool

get_tiktok_videos

Retrieve a list of TikTok videos from your Metricool account by specifying a date range and blog ID to analyze video data effectively.

Instructions

Get the list of Tiktok Videos from your Metricool account.

Args: init date: Init date of the period to get the data. The format is YYYY-MM-DD end date: End date of the period to get the data. The format is YYYY-MM-DD blog id: Blog id of the Metricool brand account.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
blog_idYes
end_dateYes
init_dateYes

Implementation Reference

  • The handler function for the 'get_tiktok_videos' tool. It fetches TikTok video data from the Metricool API within a specified date range for a given blog_id. Includes the @mcp.tool() decorator for registration and docstring for schema.
    @mcp.tool()
    async def get_tiktok_videos(init_date: str, end_date: str, blog_id: int) -> str | dict[str, Any]:
        """
        Get the list of Tiktok Videos from your Metricool account.
    
        Args:
         init date: Init date of the period to get the data. The format is YYYY-MM-DD
         end date: End date of the period to get the data. The format is YYYY-MM-DD
         blog id: Blog id of the Metricool brand account.
        """
    
        url = f"{METRICOOL_BASE_URL}/v2/analytics/posts/tiktok?from={init_date}T00%3A00%3A00&to={end_date}T23%3A59%3A59&blogId={blog_id}&userId={METRICOOL_USER_ID}&integrationSource=MCP"
    
        response = await make_get_request(url)
    
        if not response:
            return ("Failed to get Tiktok Videos")
    
        return response
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 this is a 'Get' operation, implying read-only behavior, but doesn't disclose any behavioral traits such as authentication needs, rate limits, pagination, error handling, or what the returned list includes. For a tool with zero annotation coverage, this is a significant gap in transparency.

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

Conciseness4/5

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

The description is appropriately sized and front-loaded: the first sentence states the purpose clearly, followed by a structured 'Args:' section. There's no wasted text, and it efficiently conveys necessary information in a readable format, though minor improvements in flow could elevate it.

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 complexity (3 parameters, no annotations, no output schema), the description is incomplete. It covers parameter semantics but lacks behavioral context, usage guidelines, and details on return values. For a data retrieval tool with multiple parameters, this leaves significant gaps for an AI agent to operate effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It adds meaning by explaining each parameter: 'init date' and 'end date' define the period with format YYYY-MM-DD, and 'blog id' specifies the Metricool brand account. This clarifies semantics beyond the schema's basic types, though it doesn't cover all potential nuances like valid ranges or examples.

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 tool's purpose: 'Get the list of Tiktok Videos from your Metricool account.' This specifies the verb ('Get'), resource ('Tiktok Videos'), and source ('Metricool account'). However, it doesn't differentiate from sibling tools like 'get_tiktokads_campaigns' or 'get_youtube_videos' beyond the resource name, which is why it doesn't reach 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 sibling tools, prerequisites, or specific contexts for use. The only implied usage is for retrieving TikTok videos within a date range, but this is basic and lacks explicit when/when-not instructions.

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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