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Ragalgo

kokogo100/ragalgo-mcp-server
5STDIOregistry active
Summary

This server connects Claude to daily-close financial data for Korean, US, UK, Japanese stocks and crypto, specifically designed to prevent hallucination by avoiding real-time tick noise. You get scored sentiment analysis on news, technical chart indicators, and combined snapshots through tools like get_news_scored, get_chart_stock, and get_snapshots. The scoring system returns values from negative ten to positive ten for sentiment and zero to one hundred for technical signals. Reach for this when you're building investment analysis agents that need verified post-market data rather than live trading feeds. It ships with both cloud and local stdio modes, and the free tier gives you a thousand API calls to test with.

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RagAlgo: Dynamic RAG Engine for AI Reliability

npm version npm downloads GitHub stars License: MIT MCP

"Your AI is an Analyst, NOT a Day Trader."

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

  • 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).
  • Global Market Specialist: Optimized for US, UK, JP, KR, and Crypto.

👉 Official Website (ragalgo.com)


📖 Architecture & Whitepaper

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

🏗️ Data Pipeline Architecture

Our production system on Railway processes global financial data 24/7:

┌─────────────────────────────────────────────────────────────────────────────┐
│                        RagAlgo Data Pipeline (Railway)                      │
├─────────────────────────────────────────────────────────────────────────────┤
│                                                                             │
│  📥 COLLECT              🔍 FILTER              🏷️ TAG           📊 SCORE  │
│  ─────────────          ──────────────         ─────────        ──────────  │
│  • KR-News-Collector    • filter-worker-1      • tag-worker     • Gemini-1  │
│  • US-News-Collector    • filter-worker-2      • Meta-Hierarchy • Gemini-2  │
│  • UK-News-Collector    • filter-worker-3      •   Worker       • ...       │
│  • JP-News-Collector    • ibkr_filter_worker3  │                • Gemini-7  │
│  • research-collector   │                      │                │           │
│                         │                      │                │           │
│  ════════════════════════════════════════════════════════════════════════  │
│                                    ↓                                        │
│                      📦 SNAPSHOT (Daily 18:00 KST)                          │
│                      ──────────────────────────────                         │
│                      • KR-Snapshot  • US-Snapshot                           │
│                      • UK-Snapshot  • JP-Snapshot                           │
│                      • CRY-Snapshot • Unified-Snapshot                      │
│                                    ↓                                        │
│                          🚀 SERVE (MCP Server)                              │
│                          ─────────────────────                              │
│                          • RagAlgo-Service (SSE/stdio)                      │
│                          • ragalgo-relay-server (WebSocket)                 │
│                                                                             │
└─────────────────────────────────────────────────────────────────────────────┘

RagAlgo Architecture

  • 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".


🚀 Quick Start

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

☁️ Cloud Mode (Recommended - No installation required)

{
  "mcpServers": {
    "ragalgo": {
      "url": "https://ragalgo-service-production.up.railway.app/sse",
      "env": {
        "RAGALGO_API_KEY": "YOUR_API_KEY_HERE"
      }
    }
  }
}

📦 Local Mode (Requires Node.js)

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

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


📚 Usage Examples (Cookbook)

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.

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


🌍 Supported Markets & Roadmap

RagAlgo is expanding its CKN coverage globally. Currently, US, UK, Japan, Korea, and Crypto markets are fully supported.

MarketAsset ClassStatus
🇰🇷 KoreaKOSPI / KOSDAQ🟢 Live (Real-time Sentiment & Charts)
🇺🇸 USANYSE / NASDAQ🟢 Live (Daily Scored Context)
🇯🇵 JapanNikkei 225🟢 Live (Daily Scored Context)
🇬🇧 UKLSE🟢 Live (Daily Scored Context)
🪙 CryptoGlobal (Upbit/Binance)🟢 Live (Real-time Sentiment & Charts)

🛠 Tools

⚠️ CORE CONCEPT: Scored vs Raw

  • 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.
ToolDescription
get_news_scored[RECOMMENDED] News WITH AI Sentiment Scores (-10 ~ +10). Filters out noise.
get_news[Advanced] Raw News WITHOUT scores. Includes 0-score noise. Use only if you build your own scorer.
get_chart_stock[Core] Global Stock (US/UK/JP/KR) Technical Analysis (Daily Close).
get_chart_coin[Core] Global Crypto Technical Analysis (Daily Close).
get_snapshots[Best] Market Overview (News + Chart + Trend) in one call.
get_financialsCorporate Financials (Quarterly/Yearly).
search_tagsConvert names (e.g., "Samsung") to RagAlgo Tags.

📡 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.

💬 Support

  • Website: ragalgo.com
  • Email: support@ragalgo.com
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Categories
AI & LLM ToolsFinance & Commerce
Registryactive
Packageragalgo-mcp-server
TransportSTDIO
UpdatedDec 20, 2025
View on GitHub

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