wehub-resource-sync
63 lines
2.0 KiB
Python
63 lines
2.0 KiB
Python
from mcp.server.fastmcp import FastMCP
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from finance_crew import run_financial_analysis
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# create FastMCP instance
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mcp = FastMCP("financial-analyst")
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@mcp.tool()
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def analyze_stock(query: str) -> str:
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"""
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Analyzes stock market data based on the query and generates executable Python code for analysis and visualization.
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Returns a formatted Python script ready for execution.
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The query is a string that must contain the stock symbol (e.g., TSLA, AAPL, NVDA, etc.),
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timeframe (e.g., 1d, 1mo, 1y), and action to perform (e.g., plot, analyze, compare).
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Example queries:
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- "Show me Tesla's stock performance over the last 3 months"
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- "Compare Apple and Microsoft stocks for the past year"
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- "Analyze the trading volume of Amazon stock for the last month"
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Args:
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query (str): The query to analyze the stock market data.
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Returns:
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str: A nicely formatted python code as a string.
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"""
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try:
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result = run_financial_analysis(query)
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return result
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except Exception as e:
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return f"Error: {e}"
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@mcp.tool()
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def save_code(code: str) -> str:
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"""
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Expects a nicely formatted, working and executable python code as input in form of a string.
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Save the given code to a file stock_analysis.py, make sure the code is a valid python file, nicely formatted and ready to execute.
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Args:
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code (str): The nicely formatted, working and executable python code as string.
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Returns:
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str: A message indicating the code was saved successfully.
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"""
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try:
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with open('stock_analysis.py', 'w') as f:
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f.write(code)
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return "Code saved to stock_analysis.py"
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except Exception as e:
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return f"Error: {e}"
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@mcp.tool()
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def run_code_and_show_plot() -> str:
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"""
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Run the code in stock_analysis.py and generate the plot
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"""
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with open('stock_analysis.py', 'r') as f:
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exec(f.read())
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# Run the server locally
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if __name__ == "__main__":
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mcp.run(transport='stdio') |