Ragalgo MCP Server

🚀 RagAlgo: Dynamic RAG Engine for AI Reliability

RagAlgo is an MCP Server that offers mathematically scored financial context (Korean Stocks/Crypto) to AI agents. Our focus on the "State-of-Truth" (Daily Closed Data) helps prevent AI hallucinations caused by real - time market noise.

• Analyst, Not Broker: We offer "Daily Analysis Reports" (Post - Market) instead of real - time tick data.
• Scored Context: We provide "Scores" (0 - 100) and "Zones" (Forest vs Tree) rather than raw prices.
• Korean Market Specialist: Optimized for KOSPI/KOSDAQ and Upbit (Crypto).

👉 Official Website (ragalgo.com)

🚀 Quick Start

1. Direct Run (npx)

# Run immediately without installation (Requires API Key)
npx -y @ragalgo/server

2. Claude Desktop Configuration

Add this to your config file:

• Windows: %APPDATA%\Claude\claude_desktop_config.json
• Mac: ~/Library/Application Support/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "ragalgo": {
      "command": "npx",
      "args": ["-y", "@ragalgo/server", "--stdio"],
      "env": {
        "RAGALGO_API_KEY": "YOUR_API_KEY_HERE"
      }
    }
  }
}

💡 Usage Tip

You can get a Free 1,000 Call Key instantly at RagAlgo Dashboard.

✨ Features

• Analyst, Not Broker: We provide "Daily Analysis Reports" (Post - Market), not real - time tick data.
• Scored Context: Instead of raw prices, we give you "Scores" (0 - 100) and "Zones" (Forest vs Tree).
• Korean Market Specialist: Optimized for KOSPI/KOSDAQ and Upbit (Crypto).

📚 Documentation

📖 Architecture & Whitepaper

Discover why RagAlgo is the "Hippocampus" for Agentic AI, not just another RAG.

• Vision Whitepaper (The Hook)
  • Concept: Why RagAlgo is a "Semantic Digital Twin" (SDT) using the Hippocampus analogy.
  • Value: Explains the "Self - Growing Taxonomy" and "Data Flywheel" effect.
• Technical Report (The Proof)
  • Deep Dive: Detailed anatomy of the Contextual Knowledge Network (CKN).
  • 2025 Trend: How RagAlgo serves as the memory layer for Agentic AI (e.g., PepsiCo/Salesforce Agentforce).

💡 Why "Daily Close"?

Users often ask: "Why isn't the chart data real - time?"

Because AI performs better with clarity. Real - time tick data is full of noise and volatility. If you feed an LLM raw live prices, it often hallucinates patterns that don't exist.

RagAlgo acts like a Professional Technical Analyst who works after the market closes:

1. Wait for the dust to settle (Market Close).
2. Analyze the day's battle (Daily Candle & Aux Indicators).
3. Deliver a "Confirmed Strategy" to your AI.

Use RagAlgo to build "Investment Advisors", not "High - Frequency Trading Bots".

🌍 Supported Markets & Roadmap

RagAlgo is expanding its CKN coverage globally. Currently, the Korean market and Crypto assets are fully supported.

🛠 Tools

⚠️ Important Note

• get_news_scored (Default): Returns only significant news (Scores ≠ 0). Best for AI decision making.
• get_news (Raw): Returns ALL news including noise. Use this ONLY if you need raw data feed.

📡 Real - time WebSocket (Business Tier)

For users who really need live data (e.g., for monitoring dashboards), we offer a WebSocket stream. Note: This is strictly for monitoring, not for LLM inference context.

• Access: Business Plan subscribers (Includes 30 connections).
• Address: wss://ragalgo-relay-server-1-production.up.railway.app
• Guide: See Developer Docs for implementation details.

💻 Usage Examples

We have a dedicated repository for practical examples to help you get started quickly. Please visit the RagAlgo Examples Repository.

What's Inside?

• 8 Step - by - Step Recipes: From basic data fetching to advanced AI agents.
• Skeleton Code + Prompts: Copy - paste ready resources.
• Scenarios:
  • 🐣 Basic: Get stock scores in 5 minutes.
  • 🧪 Intermediate: Verify technical signals with AI.
  • 🚀 Advanced: Build an autonomous reasoning agent (Mock Trading Audit).
  • ☕ Morning Briefing: Create a bot that emails you a daily market summary.

💡 Usage Tip

"Skeleton + Prompt" Approach: We provide the ingredients. You ask ChatGPT/Claude to cook!

📄 Support

• Website: ragalgo.com
• Email: support@ragalgo.com