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kukapay

nft-analytics-mcp

by kukapay
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Python
Remote

get_new_owners

Retrieve the count of new wallet owners for NFT collections to track adoption and growth metrics using analytics data.

Instructions

Retrieve count of new NFT owners.

Returns:
    str: Count of new wallet owners as a string, or "N/A" if no data is available,
         or error message if the query fails.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • main.py:123-137 (handler)
    The main handler function for the get_new_owners tool. It is registered via the @mcp.tool() decorator. Fetches data from Dune Analytics query ID 5140497 using the helper get_latest_result and extracts the count of new wallets from the first row of results.
    @mcp.tool()
def get_new_owners() -> str:
    """
    Retrieve count of new NFT owners.

    Returns:
        str: Count of new wallet owners as a string, or "N/A" if no data is available,
             or error message if the query fails.
    """
    try:
        data = get_latest_result(5140497)
        return data[0].get("new_wallets", "N/A")
    except Exception as e:
        return str(e)

Tool Definition Quality

B3.2/5.0
Behavior2/5

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. It mentions return values (count as string, 'N/A', or error message), which adds some context, but fails to disclose critical traits like whether this is a read-only operation, potential rate limits, authentication needs, or how 'new owners' is defined (e.g., time window). This leaves significant gaps for an agent.

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 front-loaded with the core purpose in the first sentence, followed by a concise explanation of return values. Every sentence adds value without waste, making it efficiently structured and appropriately sized for a simple tool.

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 simplicity (0 parameters, no output schema, no annotations), the description is adequate but has clear gaps. It explains the return format, which is helpful, but lacks context on usage guidelines and behavioral traits like data scope or limitations, making it minimally viable but incomplete for optimal agent use.

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?

The tool has 0 parameters, and schema description coverage is 100%, so there are no parameters to document. The description doesn't need to add parameter semantics, but it correctly avoids unnecessary details, earning a baseline high score for this dimension.

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 'Retrieve' and the resource 'count of new NFT owners', making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_unique_traders_by_collection', which might retrieve similar but distinct data about traders rather than new owners.

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 'get_unique_traders_by_collection' or other sibling tools. It lacks context about prerequisites, such as whether it applies to a specific collection or timeframe, leaving usage unclear.

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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