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MCP Server: Technical Analysis - PDF & Web Report

Multi-purpose backend server combining FastAPI and MCP capabilities for technical analysis report generation with flexible integration options.

GitHub Repo Talk to AI Agent Use Flask UI Use Excel (xlwings Lite)

What It Does

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A comprehensive technical analysis platform that combines FastAPI endpoints, Model Context Protocol (MCP) integration, and a Flask frontend:

  • Three endpoint types:
    • / - Flask-based web interface
    • /api/* - FastAPI endpoints for direct programmatic access
    • /mcp - Model Context Protocol endpoint for AI/LLM integration
  • Enhanced with MCP capabilities using the fastapi-mcp package
  • Detailed API documentation with Pydantic models
  • Both synchronous and asynchronous processing
  • Generates professional PDF and HTML reports

How to Use

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Endpoints

Base URL: https://ta.tigzig.com/ MCP (Streamable HTTP, recommended): https://ta.tigzig.com/v1/mcp/http MCP (SSE): https://ta.tigzig.com/v1/mcp/sse MCP (legacy SSE, still works): https://ta.tigzig.com/mcp API Endpoint: https://ta.tigzig.com/api

Streamable HTTP (2025-03-26) is the recommended transport for modern clients (Claude.ai, Cursor, n8n). The legacy /mcp SSE endpoint is kept for backward compatibility. If you deploy your own instance, the base URL will change according to your deployment configuration.

Access Methods

  • Web Interface: visit / for the Flask frontend
  • Direct API: make HTTP requests to /api/technical-analysis
  • MCP/LLM: connect to /mcp using any MCP-compatible client

Refer to the GitHub repository README for detailed information about request formats, response structures, and example usage.

How It Works

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Data Collection

  • Historical price data fetched from Yahoo Finance API
  • Supports both daily and weekly timeframes
  • Uses the custom Yahoo Finance FastAPI MCP server (yfin-h.tigzig.com)

Technical Analysis

  • Computes EMAs, MACD, RSI, Bollinger Bands
  • Custom chart generation for both timeframes
  • Pattern recognition algorithms

AI Integration

  • Data and charts processed by Google's Gemini Vision API
  • Comprehensive market interpretation in plain English
  • MCP exposed to any AI/LLM client

How to Replicate

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  1. Clone the repository
  2. Install dependencies: pip install -r requirements.txt
  3. Configure environment variables: 
    GEMINI_API_KEY=your_gemini_api_key
GEMINI_MODEL_NAME=gemini-2.5-flash
  4. Run the server: uvicorn main:app --host 0.0.0.0 --port 8000 --timeout-keep-alive 900

Key Dependencies

  • MCP Server: Yahoo Finance (companion service)
  • FastAPI Server: ReportLab (for PDF generation)

Resources

MCP Server: Technical Analysis

Consolidated source code for FastAPI, MCP Server and Flask UI
MCP Server: Yahoo Finance

Companion Yahoo Finance data-pull MCP server
FastAPI Server: ReportLab

Markdown-to-PDF and HTML report generator
API Docs: Technical Analysis

Interactive Swagger UI for the Technical Analysis endpoints
API Docs: Yahoo Finance

Interactive Swagger UI for the Yahoo Finance Data Pull endpoints
API Docs: ReportLab

Interactive Swagger UI for the Markdown-to-PDF endpoints
FastAPI-MCP

Tadata's package to convert any FastAPI into an MCP server
Backend Process Flow

High-level diagram of backend API call flows
Bugs,issues,questions? Drop a note: [email protected]