Skip to main content
Glama
metricool

mcp-metricool

Official
by metricool

get_network_competitors

Retrieve a list of competitors from your Metricool brand account for specified social networks and dates. Analyze insights to enhance brand strategies effectively.

Instructions

Get the list of your competitors from your Metricool brand account. Add interesting conclusions for my brand about my competitors.

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 network: Network to retrieve the competitors. The format is "twitter", "facebook", "instagram", "youtube", "twitch" and "bluesky". Only these are accepted. blog id: Blog id of the Metricool brand account. limit: Limit of competitors. By default = 10 timezone: Timezone of the post. The format is "Europe%2FMadrid". Use the timezone of the user extracted from the get_brands tool.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
blog_idYes
end_dateYes
init_dateYes
limitYes
networkYes
timezoneYes

Implementation Reference

  • The handler function for the get_network_competitors tool. It uses the @mcp.tool() decorator, defines input parameters with type hints and detailed docstring, constructs the API URL using config constants, calls make_get_request helper, and returns the response or error message.
    @mcp.tool()
    async def get_network_competitors(network: str, init_date: str, end_date: str, blog_id: int, limit: int, timezone: str) -> str | dict[str, Any]:
        """
        Get the list of your competitors from your Metricool brand account.
        Add interesting conclusions for my brand about my competitors.
    
        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
         network: Network to retrieve the competitors. The format is "twitter", "facebook", "instagram", "youtube", "twitch" and "bluesky". Only these are accepted.
         blog id: Blog id of the Metricool brand account.
         limit: Limit of competitors. By default = 10
         timezone: Timezone of the post. The format is "Europe%2FMadrid".  Use the timezone of the user extracted from the get_brands tool.
        """
    
        url = f"{METRICOOL_BASE_URL}/v2/analytics/competitors/{network}?from={init_date}T00%3A00%3A00&to={end_date}T23%3A59%3A59&blogId={blog_id}&userId={METRICOOL_USER_ID}&limit={limit}&timezone={timezone}&integrationSource=MCP"
    
        response = await make_get_request(url)
    
        if not response:
            return ("Failed to get competitors")
    
        return response
  • Creation of the FastMCP server instance named 'metricool' to which all tools, including get_network_competitors, are registered via the @mcp.tool() decorator.
    # Initialize FastMCP server
    mcp = FastMCP("metricool")
  • Helper function make_get_request used by the tool to perform authenticated HTTP GET requests to the Metricool API.
    async def make_get_request(url: str) -> dict[str, Any] | None:
        """Make a get request to the Metricool API with proper error handling."""
        headers = {
            "X-Mc-Auth": METRICOOL_USER_TOKEN,
        }
        async with httpx.AsyncClient() as client:
            try:
                response = await client.get(url, headers=headers, timeout=30.0)
                response.raise_for_status()
                return response.json()
            except Exception:
                return None
  • Configuration constants used in the tool's API URL construction: base URL, user token for auth, and user ID.
    METRICOOL_BASE_URL = "https://app.metricool.com/api"
    METRICOOL_USER_TOKEN = os.getenv("METRICOOL_USER_TOKEN")
    METRICOOL_USER_ID = os.getenv("METRICOOL_USER_ID")
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. It mentions the tool 'Add[s] interesting conclusions for my brand about my competitors,' which implies analysis or insights generation beyond a simple list. However, it fails to disclose critical behavioral traits: whether this is a read-only operation, if it requires specific permissions, rate limits, or what the output format looks like (e.g., structured data vs. text). For a tool with no annotations and complex functionality, this 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.

Conciseness3/5

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

The description is structured with a purpose statement and a parameter list, but it's somewhat verbose in parameter explanations (e.g., repeating format details). Sentences like 'Add interesting conclusions for my brand about my competitors' are vague and could be more precise. It's front-loaded with the main purpose, but the parameter section lacks bullet points or clearer organization, making it less efficient.

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 no annotations, 0% schema coverage, no output schema, and 6 parameters, the description does a fair job: it explains the purpose and parameters well. However, it misses key contextual details: no output information (what 'conclusions' entail), no behavioral disclosures (e.g., safety, permissions), and minimal sibling differentiation. For a tool with moderate complexity, this leaves gaps in completeness.

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 provides detailed semantics for all 6 parameters: formats for dates (YYYY-MM-DD), network options (e.g., 'twitter'), blog id context, default limit (10), and timezone format with a reference to 'get_brands tool'. This adds substantial meaning beyond the bare schema, covering all parameters effectively, though it could clarify 'blog id' sourcing more.

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 your competitors from your Metricool brand account. Add interesting conclusions for my brand about my competitors.' It specifies the verb ('Get'), resource ('list of your competitors'), and includes the unique aspect of generating conclusions. However, it doesn't explicitly differentiate from sibling tools like 'get_network_competitors_posts', which might retrieve competitor posts rather than lists with insights.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage by specifying parameters like 'network' and 'blog id', suggesting it's for analyzing competitors on specific social networks for a given brand. However, it lacks explicit guidance on when to use this tool versus alternatives (e.g., 'get_network_competitors_posts' for posts vs. lists) or any prerequisites. The mention of 'timezone' referencing 'get_brands tool' hints at context but isn't a clear usage rule.

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

Install Server

Other Tools

Related Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/metricool/mcp-metricool'

If you have feedback or need assistance with the MCP directory API, please join our Discord server