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mcp-metricool

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by metricool

get_brands_complete

Retrieve a detailed list of brands from your Metricool account, including competitor data for Instagram, Facebook, Twitch, YouTube, Twitter, and Bluesky. Use when specific brand details are required.

Instructions

Get the list of brands from your Metricool account. Only use this tool if the user asks specifically for his brands, in every other case use get_brands. Add to the result that the only networks with competitors are Instagram, Facebook, Twitch, YouTube, Twitter, and Bluesky.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The main handler function for the 'get_brands_complete' tool. It fetches the full brands data from the Metricool API using make_get_request and returns it along with instructions on supported competitor networks. Registered via @mcp.tool() decorator.
    @mcp.tool()
    async def get_brands_complete() -> str | dict[str, Any]:
        """
        Get the list of brands from your Metricool account. Only use this tool if the user asks specifically for his brands, in every other case
        use get_brands.
        Add to the result that the only networks with competitors are Instagram, Facebook, Twitch, YouTube, Twitter, and Bluesky.
        """
    
        url = f"{METRICOOL_BASE_URL}/v2/settings/brands?userId={METRICOOL_USER_ID}&integrationSource=MCP"
    
        response = await make_get_request(url)
    
        if not response:
            return ("Failed to get brands")
    
        return {
        "brands": response,
        "instructions": (
            "Explain that only Instagram, Facebook, Twitch, YouTube, Twitter, and Bluesky support competitors. "
        )
    }
Behavior3/5

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

No annotations are provided, so the description carries full burden. It describes the core behavior (getting brand list) and adds specific context about competitors being limited to certain networks, which is valuable behavioral information. However, it doesn't address other behavioral aspects like authentication requirements, rate limits, or error conditions.

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 reasonably concise with three sentences, but the structure could be improved. The first sentence states the purpose, the second provides usage guidelines, and the third adds behavioral context about competitors - this ordering is logical. However, the third sentence feels somewhat tacked on rather than integrated, and the description could be more polished.

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?

For a tool with no parameters, no annotations, and no output schema, the description provides adequate coverage of purpose and usage guidelines. However, it lacks information about return format, authentication requirements, error handling, or what constitutes 'complete' versus the regular get_brands tool. The competitor network information is helpful but doesn't fully compensate for other missing context.

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?

With 0 parameters and 100% schema description coverage, the baseline would be 4 even with no parameter information in the description. The description doesn't discuss parameters (which is appropriate since there are none), so it meets expectations for a parameterless tool.

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 verb 'Get' and resource 'list of brands from your Metricool account', making the purpose understandable. It distinguishes from sibling 'get_brands' by indicating this is for when users ask specifically for 'his brands', though the distinction could be more explicit about what makes this version 'complete'.

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

Usage Guidelines5/5

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

The description provides explicit guidance on when to use this tool ('Only use this tool if the user asks specifically for his brands') and when to use the alternative ('in every other case use get_brands'). This directly addresses sibling tool differentiation with clear conditional logic.

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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