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RL-MCP

by rlefko

๐Ÿš€ RL-MCP: Ryan's Model Context Protocol Server

Python FastAPI PostgreSQL Docker

๐ŸŽฏ A powerful, scalable Model Context Protocol (MCP) server built with modern Python technologies

๐ŸŒŸ What is RL-MCP?

RL-MCP is a robust Model Context Protocol server designed to provide AI models with structured access to external data and services. Think of it as a bridge ๐ŸŒ‰ that allows AI assistants to interact with your applications, databases, and APIs in a standardized, secure way.

๐ŸŽช Current Features

  • ๐Ÿ” Secure Authentication - Built-in auth system to protect your endpoints

  • ๐Ÿ“Š RESTful API - Clean, well-documented API endpoints with FastAPI

  • ๐Ÿ—„๏ธ PostgreSQL Integration - Robust database layer with SQLModel/SQLAlchemy

  • ๐Ÿณ Docker Ready - Fully containerized development and deployment

  • ๐Ÿ”„ Database Migrations - Alembic-powered schema management

  • ๐Ÿ“ˆ Health Monitoring - Built-in health checks and connection monitoring

  • ๐ŸŽจ Interactive Docs - Auto-generated API documentation

  • ๐Ÿ› ๏ธ Development Tools - Pre-commit hooks, linting, and formatting

๐Ÿ“ˆ Stock Market Intelligence

๐Ÿš€ Transform your applications with AI-powered financial intelligence

RL-MCP includes a comprehensive Stock Market Intelligence API that combines cutting-edge AI with real-time financial data:

๐Ÿง  AI-Powered Capabilities

  • ๐Ÿ” Vector Search: Semantic search across news, analysis, and market data using advanced NLP

  • ๐Ÿ“Š Sentiment Analysis: Real-time sentiment scoring for news and market content

  • ๐Ÿค– Smart Analysis: AI-driven stock analysis with confidence scoring and recommendations

  • ๐ŸŽฏ Relevance Scoring: Intelligent content ranking and filtering

๐Ÿ’น Real-Time Market Data

  • ๐Ÿ“ˆ Live Pricing: Current stock prices with change indicators and market metrics

  • ๐Ÿ“ฐ News Intelligence: Latest financial news with sentiment analysis from multiple sources

  • ๐ŸŒ Market Overview: Comprehensive market summaries with top movers and trends

  • ๐Ÿ”ฅ Trending Analysis: Most active and discussed stocks based on data volume

โšก High-Performance Architecture

  • ๐Ÿš€ Intelligent Caching: Multi-layer caching for lightning-fast responses

  • ๐Ÿ”„ Background Processing: Async data ingestion and processing

  • ๐Ÿ“Š Performance Monitoring: Built-in health checks and cache statistics

  • ๐Ÿ›ก๏ธ Enterprise-Ready: Secure, scalable, and production-ready

๐ŸŽฏ Use Cases

  • ๐Ÿค– AI Trading Assistants - Portfolio analysis and trading signals

  • ๐Ÿ“Š Financial Research - Market research and competitive intelligence

  • ๐Ÿ“ฑ Investment Apps - Smart notifications and educational content

  • ๐Ÿข Enterprise Systems - Risk management and client reporting

๐Ÿ“š Comprehensive Documentation

Explore our detailed stock market API documentation:

  • ๐Ÿ“Š - Complete guide to stock market features

  • ๐Ÿ” - Advanced semantic search capabilities

  • ๐Ÿ’ก - Real-world applications and code samples

  • ๐Ÿ”— - Complete endpoint documentation

๐Ÿš€ Future Vision

This MCP server is designed to be the foundation for AI-powered applications that need:

  • ๐Ÿค– AI Model Integration - Seamless connection between AI models and your data

  • ๐Ÿ”Œ Plugin Architecture - Extensible system for adding new capabilities

  • ๐Ÿ“ก Real-time Communication - WebSocket support for live data streaming

  • ๐ŸŒ Multi-tenant Support - Serve multiple clients with isolated data

  • ๐Ÿ” Advanced Search - Vector search and semantic querying capabilities

  • ๐Ÿ“Š Analytics Dashboard - Monitor usage, performance, and insights

๐Ÿ› ๏ธ Technology Stack

  • ๐Ÿ Backend: Python 3.12 + FastAPI

  • ๐Ÿ—„๏ธ Database: PostgreSQL with SQLModel

  • ๐Ÿณ Containerization: Docker + Docker Compose

  • ๐Ÿ”„ Migrations: Alembic

  • ๐Ÿงช Code Quality: Black, isort, pylint, pre-commit hooks

  • ๐Ÿ“š Documentation: Auto-generated OpenAPI/Swagger docs

  • ๐Ÿง  AI/ML: Sentence Transformers, Vector Search, Sentiment Analysis

๐Ÿš€ Quick Start

Prerequisites

  • ๐Ÿณ Docker and Docker Compose

  • ๐Ÿ Python 3.12+ (for local development)

  • ๐Ÿบ Homebrew (macOS) or equivalent package manager

๐ŸŽฏ One-Command Setup

Get up and running in seconds! Our setup script handles everything:

make setup-environment

This magical command will:

  • ๐Ÿ”ง Install all required dependencies

  • ๐Ÿ Create and configure a Python virtual environment

  • ๐Ÿณ Set up Docker containers

  • ๐Ÿ“ฆ Install all Python packages

  • โœ… Verify everything is working

๐Ÿƒโ€โ™‚๏ธ Running the Application

๐Ÿณ Docker Development (Recommended)

# Build and start all services make up # Or run in background docker compose up -d

Your services will be available at:

๐Ÿ Local Development

# Activate virtual environment source venv/bin/activate # Start the api and db at port 8000 make up

๐Ÿ“– API Documentation

Once running, explore the interactive API documentation:

๐Ÿ”‘ Authentication

All API endpoints require authentication. Include your auth token in requests:

curl -H "Authorization: Bearer YOUR_TOKEN" http://localhost:8000/v1/item

๐Ÿ“ˆ Stock API Quick Example

# Search for Tesla battery technology insights curl -X POST "http://localhost:8000/v1/stock/search" \ -H "Authorization: Bearer YOUR_TOKEN" \ -H "Content-Type: application/json" \ -d '{ "query": "Tesla battery technology innovations", "symbols": ["TSLA"], "similarity_threshold": 0.8, "limit": 10 }' # Get current Apple stock price curl -H "Authorization: Bearer YOUR_TOKEN" \ "http://localhost:8000/v1/stock/price/AAPL" # Get market summary curl -H "Authorization: Bearer YOUR_TOKEN" \ "http://localhost:8000/v1/stock/market/summary"

๐Ÿ—„๏ธ Database Management

๐Ÿ”„ Creating Migrations

When you modify database models:

MSG="Add new awesome feature" make migration

๐Ÿ—๏ธ Database Commands

# Start the api and db at port 8000 make up # Check database health curl http://localhost:8000/health

๐Ÿ› ๏ธ Development Workflow

๐Ÿ“ฆ Managing Dependencies

# Regenerate requirements.txt with latest versions make regen-requirements

๐Ÿงน Cleanup

# Remove all containers and volumes make clean

๐Ÿ” Code Quality

Pre-commit hooks automatically run:

  • ๐ŸŽจ Black - Code formatting

  • ๐Ÿ“‹ isort - Import sorting

  • ๐Ÿ” Pylint - Code linting

๐Ÿ—๏ธ Project Structure

rl-mcp/ โ”œโ”€โ”€ ๐Ÿ“ app/ # Main application code โ”‚ โ”œโ”€โ”€ ๐Ÿ“ api/ # API layer โ”‚ โ”‚ โ””โ”€โ”€ ๐Ÿ“ v1/ # API version 1 โ”‚ โ”‚ โ”œโ”€โ”€ ๐Ÿ“ base/ # Base models and tables โ”‚ โ”‚ โ”œโ”€โ”€ ๐Ÿ“ item/ # Item management endpoints โ”‚ โ”‚ โ””โ”€โ”€ ๐Ÿ“ stock/ # ๐Ÿ“ˆ Stock market intelligence โ”‚ โ”‚ โ”œโ”€โ”€ ๐Ÿ“ services/ # AI services (vector search, market data) โ”‚ โ”‚ โ”œโ”€โ”€ ๐Ÿ“„ routes_stock.py # Stock API endpoints โ”‚ โ”‚ โ”œโ”€โ”€ ๐Ÿ“„ models_stock.py # Data models โ”‚ โ”‚ โ””โ”€โ”€ ๐Ÿ“„ controllers_stock.py # Business logic โ”‚ โ”œโ”€โ”€ ๐Ÿ“ databases/ # Database configuration โ”‚ โ””โ”€โ”€ ๐Ÿ“„ main.py # Application entry point โ”œโ”€โ”€ ๐Ÿ“ docs/ # ๐Ÿ“š Comprehensive documentation โ”‚ โ””โ”€โ”€ ๐Ÿ“ stock/ # Stock API documentation โ”œโ”€โ”€ ๐Ÿ“ docker/ # Docker configurations โ”œโ”€โ”€ ๐Ÿ“ migrations/ # Database migrations โ”œโ”€โ”€ ๐Ÿ“ scripts/ # Utility scripts โ”œโ”€โ”€ ๐Ÿ“ utilities/ # Helper utilities โ””โ”€โ”€ ๐Ÿ“„ Makefile # Development commands

๐Ÿค Contributing

We welcome contributions! ๐ŸŽ‰

  1. ๐Ÿด Fork the repository

  2. ๐ŸŒฟ Create a feature branch

  3. โœจ Make your changes

  4. ๐Ÿงช Run tests and linting

  5. ๐Ÿ“ Submit a pull request

๐Ÿ“„ License

This project is licensed under the MIT License - see the LICENSE file for details.

๐Ÿ†˜ Support

Having issues? ๐Ÿค”


๐Ÿš€ Built with โค๏ธ for the future of AI-powered applications

Ready to revolutionize how AI models interact with your data? Let's build something amazing together! โœจ

๐Ÿ“ˆ Featuring comprehensive stock market intelligence with AI-powered semantic search, real-time data, and intelligent caching ๐Ÿค–๐Ÿ’น

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