Which integrations are available for this server?

Enables automated workflow creation for stock analysis, including daily portfolio reports, price alerts, and batch valuation through HTTP request nodes

How do I use Stock Valuation 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., "@Stock Valuation MCP Server calculate PE band for CPALL with 5-year historical data" 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.

📊 Stock Valuation MCP Server

MCP Node.js TypeScript License Docker Oracle Cloud

📖 Table of Contents

📝 About

The Stock Valuation MCP Server provides professional-grade financial analysis tools for stock valuation and investment decision-making. It integrates seamlessly with Claude Desktop and provides real-time data from Thai stock markets through the SET Watch API.

Key Capabilities

Valuation Models: PE Band Analysis, Dividend Discount Model (DDM), Discounted Cash Flow (DCF)
Real-time Data: Live stock data from SET Watch API
Financial Statements: Complete income statement, balance sheet, and cash flow analysis
Historical Analysis: Track and analyze financial ratios over time
Investment Recommendations: Data-driven buy/sell/hold suggestions
Secure Configuration: Environment-based configuration for API keys and secrets

✨ Features

📈 Valuation Tools

PE Band Analysis - Historical PE ratio analysis with fair value ranges
Dividend Discount Model (DDM) - Gordon Growth Model for dividend-paying stocks
Discounted Cash Flow (DCF) - Intrinsic value calculation using free cash flow projections

🔍 Real-Time Data Integration

SET Watch API Integration - Fetch real-time Thai stock data
Financial Statements - Complete financial statement analysis
Historical Ratios - Track PE, PBV, ROE, ROA, ROIC trends over time
Automatic Calculations - Compute key financial ratios automatically

📊 Analysis Features

Trend Analysis - Identify valuation and profitability trends
Comparative Analysis - Compare against historical averages
Investment Scoring - Generate buy/sell/hold recommendations
Risk Metrics - Altman Z-Score, Piotroski F-Score calculations

🛡️ Security & Configuration

Environment Variables - Secure API key and configuration management
Oracle Cloud Ready - Optimized for Oracle Cloud Free Tier deployment
Docker Support - Containerized deployment with environment injection
Type Safety - Full TypeScript implementation with comprehensive type definitions

🛠️ Supported Tools

Tool Category	Tool Name	Description
Valuation	`calculate_pe_band`	Calculate PE band valuation with historical data
Valuation	`calculate_ddm`	Dividend Discount Model analysis
Valuation	`calculate_dcf`	Discounted Cash Flow valuation
Data Fetching	`fetch_stock_data`	Fetch real-time stock data from SET Watch
Data Fetching	`complete_valuation`	Run all valuation models with fetched data
Financial Statements	`fetch_income_statement`	Fetch income statement data
Financial Statements	`fetch_balance_sheet`	Fetch balance sheet data
Financial Statements	`fetch_cash_flow_statement`	Fetch cash flow statement data
Financial Statements	`fetch_all_financial_statements`	Fetch all statements with ratio analysis
Historical Analysis	`fetch_historical_ratios`	Fetch historical PE, PBV, ROE, ROA, ROIC data
Historical Analysis	`analyze_historical_ratios`	Analyze trends with investment recommendations

🚀 Quick Start

Prerequisites

Node.js 18+ installed
Claude Desktop (for MCP integration)
Docker (optional, for containerized deployment)

Installation

# Clone the repository git clone <repository-url> cd myMCPserver # Install dependencies npm install # Copy environment configuration cp .env.example .env # Build the project npm run build

Claude Desktop Integration

Add to your claude_desktop_config.json:

{ "mcpServers": { "stock-valuation": { "command": "node", "args": ["C:/Programing/ByAI/myMCPserver/dist/index.js"] } } }

Restart Claude Desktop to start using the tools!

Quick Test with MCP Inspector

npm install -g @modelcontextprotocol/inspector npx @modelcontextprotocol/inspector node dist/index.js

☁️ Oracle Cloud Deployment

One-Click Deployment

# Deploy to Oracle Cloud Free Tier chmod +x scripts/deploy-oracle.sh ./scripts/deploy-oracle.sh

Manual Deployment Steps

Setup Oracle Cloud Account
- Create free tier account
- Setup compartment and VCN
- Generate SSH keys
Deploy Instance
# Using OCI CLI oci compute instance launch \ --availability-domain <your-AD> \ --compartment-id <compartment-id> \ --shape VM.Standard.A1.Flex \ --shape-config '{"memoryInGBs": "6", "ocpus": "2"}' \ --display-name stock-valuation-mcp \ --assign-public-ip true
Configure Environment
# SSH into instance ssh -i ~/.ssh/oracle_key opc@<instance-ip> # Setup Docker sudo yum install -y docker sudo systemctl start docker sudo usermod -aG docker opc # Deploy MCP Server docker run -d \ --name stock-valuation-mcp \ --restart unless-stopped \ -p 2901:2901 \ -e NODE_ENV=production \ -e SET_WATCH_API_HOST=https://your-api.com \ stock-valuation-mcp:latest

For detailed deployment instructions, see Oracle Cloud Deployment Guide.

🔗 n8n Integration

Setting up n8n

Deploy n8n
docker-compose up -d
Create HTTP Request Node
{ "method": "POST", "url": "http://YOUR-MCP-SERVER:2901/mcp", "body": { "jsonrpc": "2.0", "id": 1, "method": "tools/call", "params": { "name": "fetch_stock_data", "arguments": { "symbol": "ADVANC" } } } }

Example Workflows

Daily Analysis Report: Automatically analyze portfolio stocks every morning
Price Alerts: Get notified when stocks hit target prices
Batch Valuation: Value multiple stocks in parallel

For complete n8n integration guide, see n8n Integration Documentation.

📚 Documentation

Document	Description
Oracle Cloud Deployment	Complete guide for deploying to Oracle Cloud Free Tier
n8n Integration	Integrate with n8n for automated workflows
n8n API Examples	Ready-to-use n8n workflow examples
Troubleshooting	Common issues and solutions

⚙️ Installation

Development Mode

# Install dependencies npm install # Set up environment cp .env.example .env # Build TypeScript npm run build # Run in development npm run dev

Production Mode

# Build for production npm run clean npm run build # Run production server npm start

Docker Deployment

# Build image docker build -t stock-valuation-mcp . # Run with Docker docker run -d \ -p 2901:2901 \ -e NODE_ENV=production \ stock-valuation-mcp # Or use Docker Compose docker-compose up -d

🔧 Configuration

Environment Variables

Create a .env file based on .env.example:

# API Configuration SET_WATCH_API_HOST=https://xxxxxxxxxxxx.app # Your API host SET_WATCH_API_TIMEOUT=30000 # Server Configuration NODE_ENV=production LOG_LEVEL=info # Optional: Custom API Authentication # API_AUTH_HEADER=X-API-Key # API_AUTH_VALUE=your-api-key

Available Variables

Variable	Description	Default
`SET_WATCH_API_HOST`	SET Watch API base URL	`https://xxxx-api.vercel.app`
`SET_WATCH_API_TIMEOUT`	API request timeout (ms)	`30000`
`NODE_ENV`	Environment mode	`development`
`LOG_LEVEL`	Logging level	`info`
`API_AUTH_HEADER`	Custom auth header	(none)
`API_AUTH_VALUE`	Auth header value	(none)

📚 API Documentation

Tool Examples

1. Complete Stock Analysis

{ "tool": "complete_valuation", "arguments": { "symbol": "ADVANC", "requiredReturn": 0.10, "growthRate": 0.05, "discountRate": 0.10 } }

2. Financial Statement Analysis

{ "tool": "fetch_all_financial_statements", "arguments": { "symbol": "SCB", "period": "Quarterly" } }

3. Historical Trend Analysis

{ "tool": "analyze_historical_ratios", "arguments": { "symbol": "PTT", "period": "Quarterly" } }

Response Format

All tools return structured JSON responses including:

{ "symbol": "ADVANC.BK", "timestamp": "2024-01-20T10:30:00Z", "data": { ... }, "analysis": { ... }, "recommendation": "Buy" }

💡 Usage Examples

Example 1: Thai Stock Valuation

{ "tool": "fetch_stock_data", "arguments": { "symbol": "AOT" } }

Response: Current stock data with PE, PBV, EPS, dividend yield, ROE, etc.

Example 2: PE Band Analysis with Custom Data

{ "tool": "calculate_pe_band", "arguments": { "symbol": "AAPL", "currentPrice": 150.00, "eps": 5.00, "historicalPEs": [15, 18, 20, 22, 25, 23] } }

Response: PE band analysis with fair value range and recommendation.

Example 3: DCF Valuation

{ "tool": "calculate_dcf", "arguments": { "symbol": "GOOGL", "currentPrice": 150, "freeCashFlow": 60000000000, "sharesOutstanding": 15000000000, "growthRate": 0.08, "discountRate": 0.10, "years": 5 } }

Response: DCF analysis with 5-year projections and intrinsic value calculation.

Example 4: Historical Ratio Analysis

{ "tool": "analyze_historical_ratios", "arguments": { "symbol": "KBANK", "period": "Quarterly" } }

Response: Complete historical analysis with trends and investment recommendation.

🚀 Deployment

Oracle Cloud Free Tier

Update Deployment Script:
# Edit scripts/deploy-oracle.sh # Update your Oracle Cloud credentials
Deploy:
chmod +x scripts/deploy-oracle.sh ./scripts/deploy-oracle.sh
Configure Environment:
# On the instance docker pull <your-image> docker run -d \ -p 2901:2901 \ -e NODE_ENV=production \ -e SET_WATCH_API_HOST=https://your-api.com \ <your-image>

Docker Compose

services: stock-valuation: build: . restart: unless-stopped environment: - NODE_ENV=production - SET_WATCH_API_HOST=https://your-api.com ports: - "2901:2901" volumes: - ./logs:/app/logs

Environment-Specific Configuration

Development (.env.development):

NODE_ENV=development LOG_LEVEL=debug SET_WATCH_API_TIMEOUT=60000

Production (.env.production):

NODE_ENV=production LOG_LEVEL=warn SET_WATCH_API_TIMEOUT=10000

🏗️ Architecture

Project Structure

myMCPserver/ ├── src/ │ ├── index.ts # Main MCP server entry point │ ├── config/ # Configuration management │ │ └── index.ts # Environment variable configuration │ ├── types/ # TypeScript type definitions │ │ └── index.ts # All type definitions │ └── tools/ # MCP tool implementations │ ├── stockValuation.ts # Core valuation models │ ├── setWatchApi.ts # SET Watch API integration │ ├── financialStatements.ts # Financial statement tools │ └── historicalRatios.ts # Historical analysis tools ├── scripts/ # Deployment scripts ├── dist/ # Compiled TypeScript output ├── docs/ # Additional documentation ├── tests/ # Test files (when added) ├── docker-compose.yml # Docker configuration ├── Dockerfile # Docker image definition ├── .env.example # Environment variable template └── README.md # This file

MCP Server Architecture

┌─────────────────────────────────────┐ │ Claude Desktop │ │ │ │ │ MCP Protocol │ │ │ │ ├─────────────────────────────────────┤ │ Stock Valuation Server │ │ ┌─────────────────────────────┐ │ │ │ Tool Registry │ │ │ │ ┌─────────────────────────┐ │ │ │ │ │ Valuation Tools │ │ │ │ │ │ Data Fetching Tools │ │ │ │ │ │ Analysis Tools │ │ │ │ │ └─────────────────────────┘ │ │ │ │ ┌─────────────────┐ │ │ │ │ │ Configuration │ │ │ │ │ └─────────────────┘ │ │ │ └─────────────────────────────┘ │ │ │ │ │ ┌─────────────────┐ │ │ │ SET Watch API │◄────┘ │ └─────────────────┘ │ └─────────────────────────────────────┘

🤝 Contributing

We welcome contributions! Please follow these steps:

Development Workflow

Fork the repository
Create a feature branch (git checkout -b feature/amazing-feature)
Make your changes
Add tests if applicable
Ensure all tests pass (npm test)
Commit your changes (git commit -m 'Add amazing feature')
Push to the branch (git push origin feature/amazing-feature)
Create a Pull Request

Code Standards

Use TypeScript for all new code
Follow ESLint rules (npm run lint)
Add JSDoc comments for functions
Write tests for new features
Update documentation

Testing

# Run unit tests npm test # Run with coverage npm run test:coverage # Run in watch mode npm run test:watch

📄 License

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

🙏‍♂️ Acknowledgments

Model Context Protocol - For the MCP SDK
SET Watch - For providing the Thai stock market data API
Oracle Cloud - For the generous free tier hosting option
n8n - For workflow automation capabilities

📞 Support

📧 Create an issue for bug reports or feature requests
📖 Check Issues for known problems
📚 See Documentation for detailed guides