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Glama
N-lia

MonteWalk

by N-lia
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
NEWSAPI_KEYNoYour NewsAPI key for news aggregation (optional)
ALPACA_API_KEYYesYour Alpaca API key for paper trading
ALPACA_SECRET_KEYYesYour Alpaca secret key for paper trading

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Server capabilities have not been inspected yet.

Tools

Functions exposed to the LLM to take actions

NameDescription
health_checkB

Returns the health status of the MonteWalk server.

get_account_infoB

Get detailed Alpaca account information including equity, buying power, and day trade status.

get_priceA
Retrieves historical price data (OHLCV) for a given symbol.

Args:
    symbol: The ticker symbol (e.g., 'AAPL', 'BTC-USD').
    interval: Data interval. Valid values: "1m", "2m", "5m", "15m", "30m", "60m", "90m", "1h", "1d", "5d", "1wk", "1mo", "3mo".
    period: Data period to download. Valid values: "1d", "5d", "1mo", "3mo", "6mo", "1y", "2y", "5y", "10y", "ytd", "max".
    visualize: If True, returns a candlestick chart instead of raw data.
    
Returns:
    JSON string of OHLCV data or base64-encoded candlestick chart.
get_fundamentalsC
Retrieves core financial and fundamental data.

Args:
    symbol: The ticker symbol.
    
Returns:
    Dictionary containing fundamental data.
get_orderbookB
Fetches the current order book. 
NOTE: yfinance does not provide Level 2 data. This is a placeholder to demonstrate tool registration.

Args:
    symbol: The ticker symbol.
    
Returns:
    Message indicating unavailability.
place_orderA
Submits a market or limit order to Alpaca paper trading.

Args:
    symbol: Ticker symbol.
    side: 'buy' or 'sell'.
    qty: Quantity to trade.
    order_type: 'market' or 'limit'.
    limit_price: Required if order_type is 'limit'.
    
Returns:
    Confirmation message or error
cancel_orderB
Cancels a specific open order.

Args:
    order_id: The Alpaca order ID to cancel
    
Returns:
    Confirmation message
get_positionsA
Retrieves the current state of all held positions and cash balance.

Returns:
    Dict with 'cash' and 'positions' keys
flattenA
Immediately closes all open positions.

Returns:
    Summary of closed positions
get_order_historyC
Get order history from Alpaca.

Args:
    status: "all", "open", or "closed"
    
Returns:
    Formatted order history
portfolio_riskB

Returns annualized volatility of the portfolio.

varD

Calculates Value at Risk (VaR).

max_drawdownB

Calculates Maximum Drawdown.

monte_carlo_simulationB
Runs a Monte Carlo simulation using Geometric Brownian Motion (Log Returns).

Args:
    simulations: Number of paths to simulate.
    days: Number of days to project forward.
    visualize: If True, returns a histogram of final outcomes.
run_backtestA
Backtests a Moving Average Crossover strategy.

Args:
    symbol: Ticker symbol
    fast_ma: Fast moving average period
    slow_ma: Slow moving average period  
    start_date: Backtest start date
    end_date: Backtest end date
    visualize: If True, returns equity curve chart
walk_forward_analysisC

Performs Walk Forward Analysis on MA Crossover. Optimizes (Fast, Slow) on Train, tests on Test.

compute_indicatorsC
Calculates technical indicators for a symbol.

Args:
    symbol: Ticker symbol.
    indicators: List of indicators (e.g., ['RSI', 'MACD', 'BBANDS']).
rolling_statsB

Computes rolling mean and volatility.

get_technical_summaryC

Performs a technical analysis summary (RSI, MACD, Moving Averages). Returns a 'Buy', 'Sell', or 'Neutral' signal based on aggregated indicators.

mean_variance_optimizeC

Calculates optimal portfolio weights using Mean-Variance Optimization (Max Sharpe).

risk_parityC

Calculates weights based on Inverse Volatility (Naive Risk Parity).

log_actionA
Logs an agent action or reasoning step for audit purposes.

Args:
    action_type: Category (e.g., 'REASONING', 'TRADE_DECISION', 'ERROR').
    details: Description of the action.
get_newsB
Retrieves recent news headlines for a given symbol.

Args:
    symbol: Ticker symbol.
    max_items: Maximum number of news items to return.

Returns:
    JSON string of news articles with titles and publishers.
analyze_sentimentB
Analyzes the sentiment of a given text using FinBERT on Modal (via Public Endpoint).

Args:
    text: Text to analyze (e.g., news headline, article).

Returns:
    Dictionary with polarity, confidence, and classification.
get_symbol_sentimentC
Fetches recent news for a symbol and calculates aggregate sentiment.

Args:
    symbol: Ticker symbol.

Returns:
    Aggregate sentiment analysis of recent news.
add_to_watchlistC

Adds a symbol to the monitoring watchlist.

remove_from_watchlistC

Removes a symbol from the watchlist.

get_crypto_priceB
Gets the current price of a cryptocurrency.

Args:
    coin_id: CoinGecko ID (e.g., 'bitcoin', 'ethereum', 'solana')
    vs_currency: Currency to compare against (default: 'usd')
    
Returns:
    Dictionary with price information
get_crypto_market_dataB
Gets comprehensive market data for a cryptocurrency.

Args:
    coin_id: CoinGecko ID (e.g., 'bitcoin', 'ethereum')
    
Returns:
    Formatted string with market data
get_trending_cryptoB
Gets the top trending cryptocurrencies in the last 24 hours.

Returns:
    Formatted string with trending coins
search_cryptoC
Searches for cryptocurrencies by name or symbol.

Args:
    query: Search term (e.g., 'bitcoin', 'BTC', 'ethereum')
    
Returns:
    Formatted string with search results

Prompts

Interactive templates invoked by user choice

NameDescription
morning_briefing Generates a morning briefing prompt with Portfolio and Watchlist context.
analyze_ticker Deep dive analysis prompt for a specific ticker.
risk_analysis Comprehensive risk analysis prompt for the current portfolio.
backtest_strategy Backtesting workflow prompt.
crypto_market_update Cryptocurrency market analysis prompt.
portfolio_rebalance Portfolio rebalancing workflow prompt.
sync_watchlist Intelligent watchlist synchronization with portfolio holdings. Agent automatically adds owned symbols and optionally removes sold symbols.

Resources

Contextual data attached and managed by the client

NameDescription
get_portfolio_summary Returns a live summary of the portfolio from Alpaca (Cash, Positions, Equity).
get_watchlist_resource Returns a live view of the watchlist with current prices.
get_news_resource Returns the latest news headlines for the watchlist.
get_crypto_resource Returns the top trending cryptocurrencies.
Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

C2.8/5.0

Scored across 31 tools

Disambiguation3/5

Most tools have distinct purposes, but there is some overlap that could cause confusion. For example, 'get_price' and 'get_crypto_price' both retrieve price data but for different asset classes, and 'analyze_sentiment' and 'get_symbol_sentiment' both handle sentiment analysis with slightly different scopes. The descriptions help clarify, but an agent might misselect between similar tools.

Naming Consistency4/5

Tool names predominantly follow a consistent verb_noun pattern (e.g., 'add_to_watchlist', 'cancel_order', 'get_account_info'), with only minor deviations like 'flatten' (a verb without a noun) and 'var' (an abbreviation). The naming is readable and predictable overall, though not perfectly uniform.

Tool Count2/5

With 31 tools, the count is excessive for a trading/analysis server, leading to potential bloat. Many tools (e.g., 'max_drawdown', 'rolling_stats', 'var') could be consolidated into broader functions, and the inclusion of placeholders like 'get_orderbook' adds unnecessary complexity. A more focused set of 15-20 tools would be more appropriate.

Completeness4/5

The toolset covers a wide range of trading and analysis functions, including market data, order management, portfolio analysis, and backtesting. However, there are minor gaps, such as the lack of tools for modifying watchlist entries or handling more advanced order types (e.g., stop-loss). Overall, it supports core workflows effectively with few dead ends.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources