Octagon Stock Market Data MCP

The Octagon Stock Market Data MCP server provides specialized AI-powered stock market data and valuation analysis capabilities by integrating with advanced stock data agents. Real-time market data, comprehensive technical indicators, and unlimited market intelligence. Add unlimited stock market data functionality to any MCP client including Claude Desktop, Cursor, and other popular MCP-enabled applications.

Powered by Octagon AI - Learn more about the Stock Data Agent at docs.octagonagents.com

🏆 Why Teams Choose Octagon's Enterprise-Grade Stock Market Data API

👉 Real-time market data — Access live stock prices, trading volumes, and market indicators
👉 Comprehensive analysis — Technical indicators, valuation metrics, and performance benchmarks
👉 Unlimited queries — No rate limits on stock data requests (unlike other providers)

🚀 Core Differentiators

✅ No Rate Limits - Execute unlimited stock market data queries without restrictions
✅ Real-Time Data - Live stock prices, trading volumes, and market indicators
✅ Comprehensive Coverage - Stock indices, sector performance, and industry analysis
✅ Universal MCP Integration - Add stock market data functionality to any MCP client
✅ Advanced Analytics - Technical indicators, valuation ratios, and price patterns
✅ Multi-Market Support - NYSE, NASDAQ, and other major exchanges

Features

✅ Stock Market Data

• Real-time and historical stock prices
• Trading volumes and patterns
• Market capitalization data
• Price movements and volatility metrics

✅ Valuation Analysis

• P/E ratios by company, sector, and industry
• EV/Sales and other valuation multiples
• Analyst price targets and ratings
• Market performance benchmarks

✅ Technical Analysis

• Technical indicators and chart patterns
• Trading volume analysis
• Price trend identification
• Support and resistance levels

Get Your Octagon API Key

To use Octagon Stock Market Data MCP, you need to:

1. Sign up for a free account at Octagon
2. After logging in, from left menu, navigate to API Keys
3. Generate a new API key
4. Use this API key in your configuration as the OCTAGON_API_KEY value

Prerequisites

Before installing or running Octagon Stock Market Data MCP, you need to have npx (which comes with Node.js and npm) installed on your system.

Mac (macOS)

1. Install Homebrew (if you don't have it):

   /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"

2. Install Node.js (includes npm and npx):

   brew install node

   This will install the latest version of Node.js, npm, and npx.

3. Verify installation:

   node -v
   npm -v
   npx -v

Windows

1. Download the Node.js installer:
   • Go to https://nodejs.org/ and download the LTS version for Windows.
2. Run the installer and follow the prompts. This will install Node.js, npm, and npx.
3. Verify installation: Open Command Prompt and run:

   node -v
   npm -v
   npx -v

If you see version numbers for all three, you are ready to proceed with the installation steps below.

Installation

Running on Claude Desktop

To configure Octagon Stock Market Data MCP for Claude Desktop:

1. Open Claude Desktop
2. Go to Settings > Developer > Edit Config
3. Add the following to your claude_desktop_config.json (Replace your-octagon-api-key with your Octagon API key):

{
  "mcpServers": {
    "octagon-stock-market-data-mcp": {
      "command": "npx",
      "args": ["-y", "octagon-stock-market-data-mcp@latest"],
      "env": {
        "OCTAGON_API_KEY": "YOUR_API_KEY_HERE"
      }
    }
  }
}

4. Restart Claude for the changes to take effect

Running on Cursor

Configuring Cursor Desktop 🖥️ Note: Requires Cursor version 0.45.6+

To configure Octagon Stock Market Data MCP in Cursor:

1. Open Cursor Settings
2. Go to Features > MCP Servers
3. Click "+ Add New MCP Server"
4. Enter the following:
   • Name: "octagon-stock-market-data-mcp" (or your preferred name)
   • Type: "command"
   • Command: env OCTAGON_API_KEY=your-octagon-api-key npx -y octagon-stock-market-data-mcp

If you are using Windows and are running into issues, try cmd /c "set OCTAGON_API_KEY=your-octagon-api-key && npx -y octagon-stock-market-data-mcp"

Replace your-octagon-api-key with your Octagon API key.

After adding, refresh the MCP server list to see the new tools. The Composer Agent will automatically use Octagon Stock Market Data MCP when appropriate, but you can explicitly request it by describing your stock market data needs. Access the Composer via Command+L (Mac), select "Agent" next to the submit button, and enter your query.

Running on Windsurf

Add this to your ./codeium/windsurf/model_config.json:

{
  "mcpServers": {
    "octagon-stock-market-data-mcp": {
      "command": "npx",
      "args": ["-y", "octagon-stock-market-data-mcp@latest"],
      "env": {
        "OCTAGON_API_KEY": "YOUR_API_KEY_HERE"
      }
    }
  }
}

Running with npx

env OCTAGON_API_KEY=your_octagon_api_key npx -y octagon-stock-market-data-mcp

Manual Installation

npm install -g octagon-stock-market-data-mcp

Documentation

For comprehensive documentation on using Stock Market Data capabilities, please visit our official documentation at: https://docs.octagonagents.com

Specifically for the Stock Data Agent: Stock Data Agent Guide

The documentation includes:

• Detailed API references
• Market data methodology guidelines
• Examples and use cases
• Best practices for stock market analysis
• Advanced features and capabilities

Available Tool

octagon-stock-data-agent

Specialized agent for stock market data and valuation analysis.

The tool uses a single prompt parameter that accepts a natural language query. Include all relevant details in your prompt for optimal results.

Octagon Stock Data Agent

Model Name: octagon-stock-data-agent

Specialized agent for stock market data and analysis, providing comprehensive insights into market performance and valuation.

Capabilities

• Analyze stock price and indices movements
• Track trading volumes and patterns
• Monitor market trends
• Assess technical indicators
• Compare stock performance against benchmarks
• Provide detailed valuation insights

Use Cases

The Stock Data Agent is best for:

• Stock market research
• Equity analysis
• Trading pattern identification
• Performance benchmarking
• Identifying price catalysts
• Valuation analysis and assessment

Example Queries

Get Batch Market Cap

Fetch market capitalization data for multiple given companies.

@octagon-stock-data-agent Retrieve market capitalization data for the following companies: AAPL, MSFT, GOOG.

Get Company Market Cap

Retrieve current market capitalization data for a given company.

@octagon-stock-data-agent Get a snapshot of financial ratings for the symbol AAPL with a limit of 10 results.

Get Ratings Snapshot

Obtain a snapshot of financial ratings for a specific company.

@octagon-stock-data-agent Get a snapshot of financial ratings for the symbol AAPL with a limit of 10 results.

Get Price Target Summary

Access analysts' price-target summaries for a given company's stock.

@octagon-stock-data-agent Retrieve the analysts' price-target summary for the stock symbol AAPL.

Get Price Target Consensus

Fetch consensus analyst price targets for a specific company's stock.

@octagon-stock-data-agent Retrieve consensus price targets for the stock symbol AAPL.

Get Stock Grades

Obtain the latest stock grades from leading analysts and financial institutions for a given company.

@octagon-stock-data-agent Get the latest stock grades for the symbol AAPL from top analysts and financial institutions.

Get Sector PE Ratios

Retrieve current sector price-to-earnings ratios filtered by exchange and sector.

@octagon-stock-data-agent Retrieve the latest sector P/E ratios for 2025-02-03, filtered by exchange NASDAQ and sector Technology.

Get Industry PE Ratios

Fetch current industry price-to-earnings ratios filtered by exchange and industry.

@octagon-stock-data-agent Retrieve the latest industry P/E ratios for 2025-02-03, filtered by exchange NYSE and industry Semiconductors.

Get Sector Performance Snapshot

Obtain a snapshot of market sector performance filtered by date, exchange, and sector.

@octagon-stock-data-agent Retrieve a snapshot of market sector performance for 2025-02-03, filtered by exchange NASDAQ and sector Technology.

Get Industry Performance Snapshot

Retrieve daily industry performance overview filtered by date, exchange, and industry.

@octagon-stock-data-agent Retrieve a daily overview of industry performance for 2025-02-03, filtered by exchange NASDAQ and industry Biotechnology.

Get Historical Market Cap

Access historical market capitalization data for a given company within a specified date range.

@octagon-stock-data-agent Retrieve historical market capitalization data for AAPL from from 2025-01-01 to 2025-04-30, limited to 1000 records.

Get Historical Index Full Chart

Fetch complete historical end-of-day price data for a specified market index within a given date range.

@octagon-stock-data-agent Retrieve full historical end-of-day price data for the ^GSPC index from from 2025-01-01 to 2025-04-30.

Get Historical Index Light Chart

Obtain historical end-of-day prices for a specified market index over a given period.

@octagon-stock-data-agent Get historical end-of-day prices for the ^GSPC index from 2025-01-01 to 2025-04-30.

Get Stock Price Change

Retrieve statistics on price changes for a specific company's stock.

@octagon-stock-data-agent Get stock price change statistics for the symbol AAPL.

Get Stock Quote

Fetch a real-time stock quote for a specific company.

@octagon-stock-data-agent Get real-time stock quote for the symbol AAPL.

How to Create Effective Prompts for Stock Data Analysis

When querying stock data, consider these strategies:

1. Specify precise time ranges: Include exact date ranges to limit the data scope.

   • Example: "Analyze AAPL price movement between January 1, 2023 and March 15, 2023."

2. Indicate data granularity: Specify whether you need tick-by-tick, minute, hour, day, or other timeframes.

   • Example: "Extract hourly volume data for TSLA during market hours on February 14, 2024."

3. Clarify the metrics needed: Be specific about which data points you're interested in.

   • Example: "Calculate the average daily trading range for NVDA over the past 30 trading days."

4. Request comparative analysis: Ask for comparisons between securities or time periods.

   • Example: "Compare the daily VWAP for AMZN, GOOG, and META during the last earnings season."

5. Define visualization preferences: Specify chart types or visualization needs.

   • Example: "Generate a candlestick chart with 50-day and 200-day moving averages for SPY."

6. Focus on specific events: Target data around particular market events.

   • Example: "Analyze the trading volume pattern for MSFT in the 48 hours following their Q4 earnings announcement."

7. Include technical indicators: Specify which technical analysis metrics to calculate.

   • Example: "Calculate and plot the RSI, MACD, and Bollinger Bands for AMD over the past 3 months."

8. Request pattern identification: Ask for detection of specific price or volume patterns.

   • Example: "Identify any instances of gap up openings followed by price reversals for COIN in 2023."

Stock Data Available Fields

Market Data (Real-time & Historical)

Field	Description
Open	Opening price for the specified time period
High	Highest price reached during the specified time period
Low	Lowest price reached during the specified time period
Close	Closing price for the specified time period
Volume	Number of shares traded during the specified time period
VWAP	Volume Weighted Average Price
Timestamp	Exact time of the data point
After Hours	After-hours trading price
Pre-market	Pre-market trading price
Adjusted Close	Close price adjusted for splits and dividends
Trade Count	Number of individual trades executed
Tick Size	Minimum price movement increment
Weighted Average	Weighted average price based on specified criteria
Spread	Difference between ask and bid prices
Number of Trades	Count of executed trades within the time period
Dividend Yield	Annual dividend payments as percentage of share price
52-Week High	Highest price in the past 52 weeks
52-Week Low	Lowest price in the past 52 weeks
Average Volume	Average daily trading volume
Market Cap	Total market value of outstanding shares
Historical Market Cap	Historical market value of outstanding shares over time period
Enterprise Value	Market cap plus debt minus cash

Technical Indicators

Field	Description
Simple Moving Average (SMA)	Average price over a specified number of periods
Exponential Moving Average (EMA)	Weighted moving average giving more importance to recent prices
Relative Strength Index (RSI)	Momentum oscillator measuring speed and change of price movements
Moving Average Convergence Divergence (MACD)	Trend-following momentum indicator
Bollinger Bands	Volatility bands placed above and below a moving average
Average True Range (ATR)	Market volatility indicator
On-Balance Volume (OBV)	Volume-based momentum indicator
Stochastic Oscillator	Momentum indicator comparing closing price to price range
Fibonacci Retracement	Potential support/resistance levels based on Fibonacci sequence
Ichimoku Cloud	Collection of indicators showing support/resistance, momentum, and trend direction
Volume Profile	Distribution of volume at different price levels
Money Flow Index (MFI)	Volume-weighted RSI
Average Directional Index (ADX)	Trend strength indicator

Volatility Metrics

Field	Description
Historical Volatility	Standard deviation of price changes over a specified period
Implied Volatility	Market's forecast of likely movement derived from options prices
Average True Range (ATR)	Average of true ranges over specified time period
Beta	Measure of stock's volatility compared to the overall market
Volatility Surface	Three-dimensional plot of implied volatility across strike prices and expirations
Volatility Smile	Pattern of implied volatility across different strike prices
Volatility Term Structure	Pattern of implied volatility across different expiration dates
Volatility Skew	Difference in implied volatility between out-of-money options
CBOE Volatility Index (VIX) Data	Market's expectation of 30-day forward-looking volatility
Realized Volatility	Actual historical volatility over a specific period
Volatility Ratio	Comparison of short-term to long-term volatility

Price Pattern Analysis

Field	Description
Gap Up/Down	Price difference between previous close and current open
Support Levels	Price levels where downward trends tend to pause
Resistance Levels	Price levels where upward trends tend to pause
Price Channels	Parallel lines that contain price movement
Chart Patterns	Identified patterns such as head and shoulders, double tops, etc.
Trend Lines	Lines connecting price highs or lows to identify trends
Breakout/Breakdown Points	Prices at which security moves outside established patterns
Pivot Points	Calculated levels used to determine potential support/resistance
Price Reversals	Points where price trend changes direction
Average Daily Range	Average price movement within a trading day
Volume Spikes	Unusual increases in trading volume
Price Momentum	Rate of acceleration in price movement
Consolidation Zones	Areas where price moves sideways within a range

Company Reference Data

Field	Description
Ticker	Stock trading symbol
Company Name	Legal name of the company
Exchange	Stock exchange where the security is listed
Industry	Primary industry classification
Sector	Broader market sector classification
Market Cap	Total market value of outstanding shares
Shares Outstanding	Total number of shares issued by the company
Float	Number of shares available for public trading
Primary Exchange	Main exchange where the stock is listed
Currency	Currency in which the stock is traded
Country	Country where the company is headquartered
CIK	Central Index Key (SEC identifier)
FIGI	Financial Instrument Global Identifier
ISIN	International Securities Identification Number
CUSIP	Committee on Uniform Security Identification Procedures identifier

Corporate Actions

Field	Description
Dividends	Cash payments distributed to shareholders
Stock Splits	Division of existing shares into multiple shares
Reverse Splits	Consolidation of shares to form fewer, higher-priced shares
Spinoffs	Creation of independent company through distribution of shares
Mergers & Acquisitions	Information about corporate combinations
Rights Offerings	Issuance of rights to purchase additional shares
Symbol Changes	Updates to ticker symbols
IPO Date	Initial public offering date
Delisting Events	Removal from trading on an exchange
Name Changes	Changes to company name
Dividend Ex-Date	Date when shares begin trading without dividend rights
Dividend Record Date	Date determining which shareholders receive dividends
Dividend Payment Date	Date when dividends are actually paid
Split Ratio	Ratio for stock splits (e.g., 2:1, 3:1)

Valuation Ratios

Metric	Description
PE Ratio	Price per share divided by earnings per share
PEG Ratio	PE ratio divided by earnings growth rate
Forward PEG Ratio	Forward PE ratio divided by expected earnings growth rate
PB Ratio	Price per share divided by book value per share
PS Ratio	Price per share divided by sales per share
PCF Ratio	Price per share divided by free cash flow per share
POCF Ratio	Price per share divided by operating cash flow per share
Price to Fair Value	Current price divided by estimated fair value
EV to Sales	Enterprise value divided by sales
EV to Operating Cash Flow	Enterprise value divided by operating cash flow
EV to EBITDA	Enterprise value divided by EBITDA

Troubleshooting

1. API Key Issues: Ensure your Octagon API key is correctly set in the environment or config file.
2. Connection Issues: Make sure the connectivity to the Octagon API is working properly.
3. Rate Limiting: No rate limits apply to Stock Market Data MCP - execute unlimited queries.

License

MIT

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