get_unique_traders_by_collection
Identify and count unique buyers and sellers for NFT collections using Dune Analytics data. Generate a markdown table summarizing trader activity, customizable with a limit on the number of rows.
Instructions
Retrieve count of unique buyers and sellers for NFT collections.
Args:
limit (int, optional): Maximum number of rows to fetch from the query. Defaults to 1000.
Returns:
str: Markdown table of unique traders by collection, or error message if the query fails.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No |
Implementation Reference
- main.py:105-121 (handler)The handler function for the 'get_unique_traders_by_collection' tool. It fetches the latest results from Dune query ID 5140464, converts to a pandas DataFrame, and returns a markdown table. Includes error handling.@mcp.tool() def get_unique_traders_by_collection(limit: int = 1000) -> str: """ Retrieve count of unique buyers and sellers for NFT collections. Args: limit (int, optional): Maximum number of rows to fetch from the query. Defaults to 1000. Returns: str: Markdown table of unique traders by collection, or error message if the query fails. """ try: data = get_latest_result(5140464, limit=limit) df = pd.DataFrame(data) return df.to_markdown() except Exception as e: return str(e)
- main.py:21-44 (helper)Helper function used by the tool to fetch latest execution results from a Dune Analytics query using the Dune API.def get_latest_result(query_id: int, limit: int = 1000) -> list: """ Fetch the latest results from a Dune Analytics query. Args: query_id (int): The ID of the Dune query to fetch results from. limit (int, optional): Maximum number of rows to return. Defaults to 1000. Returns: list: A list of dictionaries containing the query results, or an empty list if the request fails. Raises: httpx.HTTPStatusError: If the API request fails due to a client or server error. """ url = f"{BASE_URL}/query/{query_id}/results" params = {"limit": limit} with httpx.Client() as client: response = client.get(url, params=params, headers=HEADERS, timeout=300) response.raise_for_status() data = response.json() result_data = data.get("result", {}).get("rows", []) return result_data