Which integrations are available for this server?

Supplies sanitized financial data feeds in non-scored mode for custom agent pipelines and workflows. Provides raw financial data feeds for workflow automation with sanitized news, market data, and tag-based search capabilities.

How do I use RagAlgo MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@RagAlgo MCP Server show me recent bullish news for Samsung Electronics" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

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:

Wait for the dust to settle (Market Close).
Analyze the day's battle (Daily Candle & Aux Indicators).
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.

Market	Asset Class	Status
🇰🇷 Korea	KOSPI / KOSDAQ	🟢 Live (Real-time Sentiment & Charts)
🇺🇸 USA	NYSE / NASDAQ	🟢 Live (Daily Scored Context)
🇯🇵 Japan	Nikkei 225	🟢 Live (Daily Scored Context)
🇬🇧 UK	LSE	🟢 Live (Daily Scored Context)
🪙 Crypto	Global (Upbit/Binance)	🟢 Live (Real-time Sentiment & Charts)

🛠 Tools

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

Tool	Description
`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_financials`	Corporate Financials (Quarterly/Yearly).
`search_tags`	Convert 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.