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This guide requires an installation of Python and fastmcp library. If you do not know what that is; this guide is not intended for you.

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Ensure that FastMCP is installed

Run pip install fastmcp and read the FastMCP documentation.

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Set provided Statista configuration details

mcp_api_key = "<YOUR_API_KEY>"
mcp_server_url = "<PROVIDED_MCP_SERVER_URL>"

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Run example client

from fastmcp import Client
from fastmcp.client.transports import StreamableHttpTransport

import asyncio
import json

mcp_client = Client(
    transport=StreamableHttpTransport(
        mcp_server_url,
        headers={"x-api-key": mcp_api_key},
    ),
)

async def main():
    async with mcp_client as client:
        # List available tools
        tools = await client.list_tools()
        
        # Call search-statistics with a natural language query
        statistics = await client.call_tool("search-statistics", 
                                            {"question": "What's the GDP of Japan?"})
        print(json.loads(statistics.content[0].text))

        # grab the first statistic id
        grab_statistic_id = json.loads(statistics.content[0].text)["items"][0]["identifier"]
        
        # fetch chart data for a specific statistic id
        statistic_chart_data = await client.call_tool("get-chart-data-by-id", 
                                            {"statistic_id": int(grab_statistic_id)})
        
        statistic_id = json.loads(statistic_chart_data.content[0].text)
        chart_data = json.loads(statistic_chart_data.content[1].text)
    
if __name__ == "__main__":
    asyncio.run(main())