MonteWalk
MonteWalk is an institutional-grade quantitative trading MCP server that transforms AI assistants into professional trading terminals with real-time market data, paper trading, risk analytics, and advanced visualizations.
Market Data & Intelligence: Retrieve historical OHLCV price data with customizable intervals, fundamentals, real-time cryptocurrency prices and market data, trending coins, news headlines, sentiment analysis using FinBERT, and scan for unusual market activity.
Trading & Portfolio Management (Paper Trading): Access Alpaca paper trading account information (equity, buying power, day trade status), place/cancel market or limit orders, view open positions and cash balance, close all positions, retrieve order history, and manage an intelligent watchlist with auto-sync.
Risk Analytics: Calculate portfolio volatility, Value at Risk (VaR) at specified confidence levels, maximum drawdown, and run Monte Carlo simulations for portfolio path forecasting with histogram visualizations.
Technical Analysis: Compute 20+ indicators (RSI, MACD, Bollinger Bands, moving averages), generate automated Buy/Sell/Neutral signals, and perform rolling statistics.
Backtesting & Optimization: Test moving average crossover strategies with equity curve visualization, perform walk-forward analysis for overfitting prevention, and optimize portfolio weights using Mean-Variance (Max Sharpe) and Risk Parity algorithms.
Visualization: Generate candlestick charts, equity curves, histograms, and other chart types with dark theme styling, returned as base64-encoded images.
Agent Utility: Log agent actions and reasoning steps for audit trails, and utilize pre-built agentic prompts for complex analyses like Morning Briefing, Gamma Hunt, Ticker Analysis, and Portfolio Rebalancing.
System Status: Perform health checks to verify server operational status.
Total: 30 tools across 9 categories providing comprehensive quantitative trading capabilities for AI-powered workflows.
Enables deployment of the MCP server with a Gradio UI interface on Hugging Face's platform for web-based access to quantitative finance tools.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MonteWalkrun a Monte Carlo simulation on my portfolio with 10,000 iterations"
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.
title: MonteWalk emoji: ποΈ colorFrom: blue colorTo: purple sdk: gradio sdk_version: 6.0.0 app_file: app.py pinned: true tags:
building-mcp-track-enterprise
building-mcp-track-consumer
MODAL.com
ποΈ MonteWalk
Institutional-grade quantitative trading tools for AI agents
Built for the MCP 1st Birthday Hackathon π
π MCP Server Stats:
π οΈ 25+ Tools | π‘ 4 Resources | π― 6 Agentic Prompts
π― The Problem
Retail traders face an overwhelming flood of market data, news, and analysis toolsβbut lack the institutional-grade infrastructure to make sense of it all:
Data Overload: Thousands of stocks, crypto assets, news sourcesβimpossible to monitor manually
Risk Blindness: No access to professional risk metrics (VaR, drawdown, Monte Carlo)
Execution Friction: Scattered tools across multiple platforms, no unified workflow
AI Disconnect: Existing AI assistants can't access real-time market data or execute trades
What if your AI assistant could be your quantitative analyst, risk manager, and trading deskβall in one?
β¨ The Solution
MonteWalk is a Model Context Protocol (MCP) server that transforms AI assistants like Claude into institutional-grade trading terminals. It provides:
π MCP Integration
Connect to Claude Desktop, VSCode, or any MCP-compatible client to give your AI:
Real-time market data (stocks, crypto, news)
Portfolio management and execution
Risk analytics and backtesting
Intelligent workflows and automation
π¨ Beautiful Gradio 6 Interface
Test all tools through a polished, professional UI featuring:
Live Dashboard: Portfolio, watchlist, crypto trends, news feed
Interactive Toolbox: Direct access to 25+ trading tools
MCP Client Setup: Copy-paste configuration for instant connection
Dark Theme: Sleek glassmorphism design with smooth animations
π§ Agentic Workflows
Pre-built prompts that guide AI through complex multi-step analyses:
Morning Briefing: Portfolio review, market scan, risk check
Gamma Hunt: Find unusual market activity and deep-dive top picks
Ticker Analysis: Comprehensive research (fundamentals, technicals, sentiment)
Portfolio Rebalancing: Optimize weights using modern portfolio theory
π Key Features
π Market Intelligence
Multi-source Data: Yahoo Finance, Alpaca, CoinGeckoβall cached for speed
Crypto Support: Live prices, trending coins, comprehensive market data
News Aggregation: yfinance β NewsAPI β GNews fallback pipeline
Sentiment Analysis: FinBERT-powered financial sentiment scoring (via Modal)
Unusual Activity Scanner: Detect big movers, volume spikes, reversal candidates
π Advanced Visualizations
Candlestick Charts: Professional OHLC charts with volume bars
Interactive Charts: Line, bar, histogram, scatter, heatmap support
Dark Theme: Charts styled to match UI with custom color palette
Base64 Encoding: Charts returned as embeddable images for AI consumption
Integrated with Tools:
get_price(visualize=True),monte_carlo_simulation(visualize=True), etc.
β‘ Paper Trading Engine
$100K Virtual Capital: Risk-free strategy testing on Alpaca Paper Trading
Smart Execution: Simulated slippage and transaction costs
Pre-trade Risk Checks: Prevents portfolio concentration >50%
Position Management: Instant portfolio view and one-click flatten
π‘οΈ Institutional Risk Analytics
Value at Risk (VaR): Historical simulation at any confidence level
Monte Carlo Forecasting: GBM-based portfolio path simulations
Volatility Metrics: Annualized portfolio standard deviation
Drawdown Analysis: Track maximum peak-to-trough decline
π¬ Professional Backtesting
Walk-Forward Analysis: Out-of-sample validation to prevent overfitting
Strategy Lab: Test MA crossovers, custom indicators, any logic
Transaction Costs: Realistic modeling with slippage and fees
π Technical Analysis Suite
Smart Signals: Automated Buy/Sell/Neutral recommendations
20+ Indicators: RSI, MACD, Bollinger Bands, SMAs, and more
Portfolio Optimization: Mean-variance, risk parity algorithms
π― Intelligent Watchlist
Auto-sync: Detects owned stocks not in watchlist and prompts addition
Live Prices: Real-time updates for tracked symbols
News Feed: Aggregated headlines for all watched assets
π¨ UI/UX Showcase
MonteWalk features a professionally designed Gradio 6 interface optimized for traders:
Landing Page
Hero Section: Clear value proposition with feature cards
Glassmorphism Design: Modern dark theme with subtle transparency
Smooth Navigation: Instant page transitions with scroll-to-top
Dashboard
4-Panel Layout: Portfolio, Watchlist, Crypto, Newsβall in one view
One-Click Refresh: Update all data sources simultaneously
Responsive Design: Works seamlessly on desktop and tablet
Toolbox
Organized by Category: 9 tool groups with collapsible accordions
Dynamic Forms: Auto-generated from function signatures
Clear Results: Formatted outputs with syntax highlighting
Settings
API Configuration: Secure credential management with password fields
Instant Feedback: Clear success/error messages
Restart Prompt: Guides users on applying changes
π§ Technical Implementation
Built with Gradio 6
Native MCP Support:
demo.launch(mcp_server=True)enables seamless integrationCustom Theming: Professional dark palette using
gr.themes.BaseAdvanced CSS: Glassmorphism effects, custom animations, responsive grid
Navigation State: Visibility control for multi-page SPA experience
MCP Architecture
25+ Tools: Comprehensive trading toolkit spanning 9 categories
4 Resources: Live portfolio, watchlist, news, crypto feeds
6 Prompts: Guided workflows for complex multi-step analyses
Error Resilience: Automatic fallbacks and graceful degradation
Data Pipeline
Caching Strategy: 5-minute TTL on market data requests
Multi-source Fallback: yfinance β NewsAPI β GNews β CoinGecko
FinBERT Sentiment: Serverless GPU inference via Modal endpoint
Local Storage: JSON-based portfolio and watchlist persistence
Visualization System
Matplotlib + Seaborn: Professional charts with dark theme
6 Chart Types: Candlestick, line, bar, histogram, scatter, heatmap
mplfinance Integration: Specialized candlestick rendering with volume
Base64 Images: Charts encoded for AI/web consumption
Tool-Integrated: Optional
visualizeparameter in key functions
Market Scanner
3 Scan Types: Big movers, volume spikes, reversal candidates
Real-time Data: Powered by Alpaca market data API
Smart Filtering: Configurable thresholds and limits
Visualization Support: Bar charts for scan results
Security & Safety
Paper Trading Only: Zero real money risk
Environment Variables: API keys never committed to code
Position Limits: Hard-coded risk checks on every trade
Audit Logging: Complete action trail with timestamps
π Real-World Impact
MonteWalk democratizes institutional-grade quantitative finance for retail traders and developers:
For Individual Traders
Learn by Doing: Practice strategies with $100K virtual capital
Risk Education: Understand VaR, drawdown, volatility in real-time
Time Savings: Automate research with AI-powered workflows
Better Decisions: Combine fundamentals, technicals, and sentiment
For Developers
MCP Template: Reference implementation for financial tool servers
Gradio Best Practices: Professional UI patterns with Gradio 6
API Integration: Multi-source data aggregation examples
Testing Framework: Safe paper trading environment for strategy validation
For AI Assistants
Context Enhancement: Give Claude/GPT financial superpowers
Agentic Workflows: Enable complex multi-step trading strategies
Real-time Data: Connect LLMs to live market information
Tool Orchestration: Demonstrate MCP's composability potential
Potential Extensions
Live Trading: Production Alpaca integration (easy switch from paper)
Advanced Strategies: Options, futures, arbitrage implementations
Social Trading: Share and clone successful agent workflows
Educational Platform: Interactive finance courses powered by AI
π₯ Demo Video
Coming Soon: Full walkthrough of MonteWalk's features, MCP integration, and agentic workflows.
π Quick Start
Option 1: Try on Hugging Face Spaces (Recommended)
Click the Gradio UI above to:
Explore the dashboard and toolbox
View MCP client setup instructions
Test tools directly in your browser
Option 2: Run Locally
Prerequisites
Python 3.12+
uv (optional, recommended)
Alpaca Paper Trading Account (free)
NewsAPI Key (optional, 100 free requests/day)
Installation
git clone https://github.com/N-lia/MonteWalk.git
cd MonteWalk
# Option 1: Using uv (recommended) - handles venv creation and dependency install
uv sync
# Option 2: Using pip
# python3 -m venv .venv
# source .venv/bin/activate # Windows: .venv\Scripts\activate
# pip install -r requirements.txtConfiguration
cp .env.example .env
# Edit .env with your API keys:
# ALPACA_API_KEY=your_key
# ALPACA_SECRET_KEY=your_secret
# NEWSAPI_KEY=your_key (optional)Run
# Gradio UI + MCP Server
uv run app.py
# Or pure MCP Server (for Claude Desktop)
uv run server.pyOption 3: Connect to Claude Desktop
1. Add to claude_desktop_config.json:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"montewalk": {
"command": "/absolute/path/to/MonteWalk/.venv/bin/python",
"args": ["/absolute/path/to/MonteWalk/server.py"]
}
}
}2. Restart Claude Desktop
3. Start using MonteWalk:
"What's my portfolio risk?"
"Analyze AAPL technicals and sentiment"
"Backtest a 10/50 MA crossover on MSFT"
"Run morning briefing"
π Documentation
API Reference: Complete tool documentation with examples
.env.example: Configuration template
ποΈ Architecture
MonteWalk/
βββ app.py # Gradio 6 UI + MCP server
βββ server.py # Pure MCP server (stdio)
βββ theme.py # Custom Gradio theme
βββ config.py # Environment config
βββ tools/ # 25 trading tools
β βββ market_data.py
β βββ execution.py
β βββ risk_engine.py
β βββ backtesting.py
β βββ feature_engineering.py
β βββ portfolio_optimizer.py
β βββ news_intelligence.py
β βββ watchlist.py
β βββ crypto_data.py
β βββ ...
βββ resources/ # Educational materials
βββ data/ # Local storage (gitignored)Tech Stack
Frontend: Gradio 6.0, Custom CSS, Google Fonts
MCP: FastMCP, stdio/HTTP protocols
Data: yfinance, Alpaca SDK, CoinGecko, NewsAPI
Analysis: NumPy, SciPy, Pandas, pandas_ta
Sentiment: FinBERT (Modal serverless GPU)
Deployment: Hugging Face Spaces, Python 3.12
π Learn More
Model Context Protocol: modelcontextprotocol.io
Gradio 6 Docs: gradio.app/docs
Alpaca Paper Trading: alpaca.markets/docs/trading/paper-trading
π Acknowledgments
Built for the MCP 1st Birthday Hackathon by N-lia.
Special thanks to:
Anthropic for the Model Context Protocol specification
Gradio for the amazing UI framework and MCP support
Alpaca for free paper trading infrastructure
Modal for serverless GPU inference
π License
MIT License - see LICENSE for details.
π Links
GitHub: github.com/N-lia/MonteWalk
Hugging Face Space: huggingface.co/spaces/N-lia/MonteWalk
MCP 1st Birthday: huggingface.co/spaces/launch/mcp-1st-bday
Made with β€οΈ for the trading community
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