Model Context Protocol (MCP) server for stock traders
This MCP server offers comprehensive stock analysis features like technical indicators, pattern recognition, volume profile, and risk tools for traders and developers.
Added on:
Created by:
Mar 07 2025
This MCP server offers comprehensive stock analysis features like technical indicators, pattern recognition, volume profile, and risk tools for traders and developers.
Added on:
Created by:
Mar 07 2025
Seth Hobson
Featured
What is Model Context Protocol (MCP) server for stock traders?
The MCP trader server enables stock traders and developers to perform in-depth technical analysis, pattern detection, and risk management. It provides tools such as analyze-stock for technical analysis, relative-strength for performance comparison, volume-profile for volume distribution analysis, and detect-patterns for chart pattern recognition. The server leverages Tiingo API data and supports setups via Python, Docker, and Smithery. It aims to facilitate automated trading strategies, portfolio analysis, and real-time data integration, making it suitable for quantitative traders and financial developers seeking customizable technical and pattern analysis features.
Who will use Model Context Protocol (MCP) server for stock traders?
- Stock traders
- Quantitative analysts
- Financial developers
- Trading algorithm designers
How to use the Model Context Protocol (MCP) server for stock traders?
- Step 1: Install dependencies including Python, Docker, or Smithery
- Step 2: Configure API keys and environment variables
- Step 3: Run the MCP server via Docker or local setup
- Step 4: Use REST endpoints or integrated tools for analysis in software or IDE
- Step 5: Input stock symbols and parameters to perform technical analysis or pattern detection
Model Context Protocol (MCP) server for stock traders's Core Features & Benefits
The Core Features
- analyze-stock
- relative-strength
- volume-profile
- detect-patterns
- position-size
- suggest-stops
The Benefits
- Enables automated and detailed stock technical analysis
- Provides pattern detection with confidence scores
- Supports risk management through position sizing and stop suggestions
- Integrates with trading workflows via REST API
- Customizable setup via Smithery, Docker, or direct Python environment
Model Context Protocol (MCP) server for stock traders's Main Use Cases & Applications
- Automated stock analysis for trading decisions
- Pattern recognition for chart setups
- Risk management and position sizing in trading algorithms
FAQs of Model Context Protocol (MCP) server for stock traders
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