Ragalgo

RagAlgo: Dynamic RAG Engine for AI Reliability

"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)](https://www.ragalgo.com)

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📖 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) │ │ │ └─────────────────────────────────────────────────────────────────────────────┘

• [Vision Whitepaper (The Hook)](./docs/RagAlgo_Report_EN.md)
• 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)](./docs/CKN_Architecture_EN.md)
• 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).

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💡 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".

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🚀 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.

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📚 Usage Examples (Cookbook)

We have a dedicated repository for practical examples to help you get started quickly. Please visit the [RagAlgo Examples Repository](https://github.com/kokogo100/ragalgo-examples).

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!

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🌍 Supported Markets & Roadmap

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

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🛠 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.

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📡 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.

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💬 Support

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