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by metricool

get_x_posts

Retrieve X (Twitter) posts from a Metricool account within a specified date range using start date, end date, and blog ID. Simplify social media data extraction for analysis or reporting.

Instructions

Get the list of X (Twitter) Posts from your Metricool account.

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

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
blog_idYes
end_dateYes
init_dateYes

Implementation Reference

  • The core handler function for the 'get_x_posts' tool. It is registered via the @mcp.tool() decorator. Fetches X (formerly Twitter) posts data from the Metricool API using a GET request to the /stats/twitter/posts endpoint, with parameters for date range and blog ID. Returns the API response or an error message if the request fails.
    @mcp.tool()
    async def get_x_posts(init_date: str, end_date: str, blog_id: int) -> str | dict[str, Any]:
        """
        Get the list of X (Twitter) Posts from your Metricool account.
    
        Args:
         init date: Init date of the period to get the data. The format is YYYYMMDD
         end date: End date of the period to get the data. The format is YYYYMMDD
         blog id: Blog id of the Metricool brand account.
        """
    
        url = f"{METRICOOL_BASE_URL}/stats/twitter/posts?start={init_date}&end={end_date}&blogId={blog_id}&userId={METRICOOL_USER_ID}&integrationSource=MCP"
    
        response = await make_get_request(url)
    
        if not response:
            return ("Failed to get X Posts")
    
        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 full burden for behavioral disclosure. It states the tool retrieves data ('Get'), implying a read-only operation, but doesn't clarify permissions, rate limits, pagination, or response format. For a data-fetching tool with zero annotation coverage, this lack of behavioral details is a significant gap.

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 core purpose, followed by a structured 'Args:' section for parameters. Every sentence adds value without redundancy. Minor improvements could include briefer formatting, but overall it's efficient and well-organized.

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 (3 parameters, no output schema, no annotations), the description is partially complete. It covers purpose and parameter semantics well, but lacks behavioral details (e.g., response format, error handling) and usage guidelines. This makes it adequate for basic use but insufficient for robust agent decision-making.

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 meaningful semantics by explaining all three parameters: 'init date' and 'end date' define a period with format 'YYYYMMDD', and 'blog id' specifies the 'Metricool brand account'. This goes beyond the schema's basic titles and types, providing crucial context for correct usage.

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 X (Twitter) Posts from your Metricool account.' It specifies the verb ('Get'), resource ('X (Twitter) Posts'), and source ('Metricool account'), which is clear and specific. However, it doesn't explicitly differentiate from sibling tools like 'get_analytics' or 'get_metrics' that might also retrieve data from Metricool, preventing 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 like 'get_analytics' or 'get_metrics' for comparison, nor does it specify prerequisites (e.g., authentication needs) or contextual triggers. The absence of usage context leaves the agent without clear selection criteria.

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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