ManaMurah MCP Server

A Model Context Protocol (MCP) server for Malaysian price data from KPDN Pricecatcher. This server enables direct integration with Claude Desktop and other MCP-compatible AI tools for querying Malaysian consumer goods prices.

Features

🇲🇾 Official Malaysian Price Data - KPDN Pricecatcher data via OpenDOSM
🤖 AI-Optimized - Natural language queries with intelligent parsing
⚡ Serverless - Deployed on Cloudflare Workers for global performance
🔒 Rate Limited - Built-in abuse protection and fair usage
📊 Rich Analytics - Price comparisons, trends, and market insights
🎯 Claude Desktop Ready - One-click setup for Claude Desktop integration

Related MCP server: Weather MCP MY

Live Demo

The MCP server is deployed and accessible at:

• Production: https://mcp.manamurah.com

• API Endpoint: https://mcp.manamurah.com/mcp

• Status: https://mcp.manamurah.com/ (returns server info)

Quick Start

Deploy to Cloudflare Workers

# Clone or create from template
npm create cloudflare@latest manamurah-mcp-server --template=cloudflare/ai/demos/remote-mcp-authless

# Replace src/ contents with ManaMurah implementation
# (Copy files from this directory)

# Install dependencies
npm install

# Deploy to Cloudflare Workers
npm run deploy

Connect to Claude Desktop

1. Get your deployed Workers URL (e.g., https://mcp.manamurah.com)

2. Add to Claude Desktop MCP configuration:

{
  "manamurah": {
    "command": "node",
    "args": ["/path/to/mcp-client.js"],
    "env": {
      "MCP_SERVER_URL": "https://mcp.manamurah.com/sse"
    }
  }
}

3. Restart Claude Desktop

4. Start asking about Malaysian prices!

Available Tools

🔍 get_malaysian_prices

Search for current prices with natural language queries.

Examples:

• "rice prices in Kuala Lumpur"

• "cheapest chicken in Penang hypermarkets"

• "cooking oil under RM20 in Selangor"

📊 compare_prices

Compare prices across different regions or retail chains.

Examples:

• Compare rice prices between KL and Penang

• Find price differences across retail chains

• Regional price analysis for specific items

📈 analyze_price_trends

Analyze price trends and market patterns over time.

Examples:

• Price volatility analysis

• Seasonal price patterns

• Regional market trends

💡 get_market_insights

Get market intelligence and insights about price anomalies.

Examples:

• Recent price changes

• Market anomaly detection

• Regional price differences

Example Usage

Basic Price Search

User: "What are rice prices in Kuala Lumpur?"

MCP Response:
📊 Summary: Rice prices in Kuala Lumpur range from RM15.20-RM25.80 per 5kg

💡 Key Insights:
• Hypermarkets offer 18% lower prices than convenience stores
• Significant price variation exists across different retailers

📈 Price Statistics:
• Average: RM18.50
• Range: RM15.20 - RM25.80
• Price Variation: 32%

[Detailed price listings follow...]

Price Comparison

User: "Compare chicken prices between Penang and Johor"

MCP Response:
📊 Summary: Penang has lower average chicken prices (RM8.20) compared to Johor (RM9.10)

## Regional Comparison

### 1. Penang
• Average Price: RM8.20
• Price Range: RM7.50 - RM9.80
• Sample Size: 15 price points

### 2. Johor
• Average Price: RM9.10
• Price Range: RM8.20 - RM11.50
• Sample Size: 12 price points

💡 Comparison Insights:
• Most Affordable: Penang (RM8.20 average)
• Potential Savings: RM0.90 (9.9%) by choosing Penang

Development

Local Development

# Install dependencies
npm install

# Start development server
npm run dev

# Type checking
npm run type-check

# Linting
npm run lint

Project Structure

src/
├── index.ts                 # Main MCP server implementation
├── utils/
│   ├── api-client.ts        # ManaMurah API client
│   ├── query-parser.ts      # Natural language query parsing
│   ├── response-formatter.ts # MCP response formatting
│   └── rate-limiter.ts      # Rate limiting implementation
└── types/
    └── manamurah.ts         # TypeScript type definitions

Configuration

Environment variables in wrangler.toml:

[vars]
MANAMURAH_API_BASE = "https://api.manamurah.com"
RATE_LIMIT_ENABLED = "true"
CACHE_TTL = "300"
MAX_QUERIES_PER_MINUTE = "10"
MAX_QUERIES_PER_HOUR = "100"

Rate Limits

• Per Minute: 10 requests

• Per Hour: 100 requests

• Automatic Cleanup: Old request data is cleaned up automatically

Rate limits help ensure fair usage and prevent abuse while allowing genuine research and analysis.

Features

Natural Language Processing

• Intelligent extraction of items, locations, and price constraints

• Support for Malaysian terms (e.g., "beras" for rice, "ayam" for chicken)

• Price range detection ("under RM20", "between RM10 and RM15")

• Location recognition for all Malaysian states and major cities

Rich Response Formatting

• Markdown-formatted responses optimized for Claude Desktop

• Statistical analysis with averages, ranges, and insights

• Suggested follow-up questions for continued exploration

• Data source attribution and freshness indicators

Error Handling

• User-friendly error messages with helpful suggestions

• Graceful degradation when data is unavailable

• Query improvement recommendations

• Comprehensive error logging for debugging

Data Source

Official Government Data: KPDN Pricecatcher program via OpenDOSM

• Daily data updates (subject to government publication schedules)

• Comprehensive coverage of Malaysian retail prices

• Data includes hypermarkets, supermarkets, convenience stores, and grocery shops

• Covers all Malaysian states and major urban centers

Support

Getting Help

• Documentation: api.manamurah.com/docs

• AI Integration Guide: Complete guide for AI developers

• Issues: GitHub Issues

Contact

• General Support: support@manamurah.com

• AI Integration: ai-support@manamurah.com

• Enterprise: enterprise@manamurah.com

License

MIT License - see LICENSE file for details.

Contributing

Contributions welcome! Please read our contributing guidelines and submit pull requests for any improvements.

Built with ❤️ for the Malaysian data community

Making Malaysian price data accessible to AI tools and researchers worldwide.