Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| MCP_HOST | No | Server host address | 0.0.0.0 |
| MCP_PATH | No | HTTP endpoint path | /mcp |
| MCP_PORT | No | Server port number | 8000 |
| LOG_LEVEL | No | Logging verbosity level | INFO |
| MCP_TRANSPORT | No | Transport method for the server | streamable-http |
| QUANTCONNECT_USER_ID | Yes | Your QuantConnect user ID (required for authentication) | |
| QUANTCONNECT_API_TOKEN | Yes | Your QuantConnect API token found in settings | |
| QUANTCONNECT_ORGANIZATION_ID | No | Optional organization ID for QuantConnect |
Schema
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
| system_info | Get comprehensive system information. |
| server_status | Get QuantConnect MCP server status and statistics. |
| tools_summary | Get summary of available QuantConnect tools. |
| performance_metrics | Get server performance metrics. |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| configure_quantconnect_auth | Configure QuantConnect API authentication credentials.
Args:
user_id: Your QuantConnect user ID (from email)
api_token: Your QuantConnect API token (from Settings page)
organization_id: Your organization ID (from organization URL)
Returns:
Dictionary containing authentication configuration status
|
| validate_quantconnect_auth | Validate current QuantConnect authentication configuration.
Returns:
Dictionary containing authentication validation results
|
| get_auth_status | Get current authentication status and configuration.
Returns:
Dictionary containing authentication status information
|
| test_quantconnect_api | Test QuantConnect API connectivity with current authentication.
Args:
endpoint: API endpoint to test (default: authenticate)
method: HTTP method to use (default: POST)
Returns:
Dictionary containing API test results
|
| clear_quantconnect_auth | Clear current QuantConnect authentication configuration.
Returns:
Dictionary containing operation status
|
| get_auth_headers_info | Get information about authentication headers (without exposing sensitive data).
Returns:
Dictionary containing header information
|
| create_project | Create a new project in your QuantConnect organization.
Args:
name: Project name (must be unique within organization)
language: Programming language - "C#" or "Py" (default: "Py")
organization_id: Optional organization ID (uses default if not specified)
Returns:
Dictionary containing project creation result with project details
|
| read_project | Read project details by ID or list all projects if no ID provided.
Args:
project_id: Optional project ID to get specific project details.
If not provided, returns list of all projects.
Returns:
Dictionary containing project details or list of all projects
|
| update_project | Update a project's name and/or description.
Args:
project_id: ID of the project to update
name: Optional new name for the project
description: Optional new description for the project
Returns:
Dictionary containing update result
|
| create_file | Create a new file in a QuantConnect project.
Args:
project_id: ID of the project to add the file to
name: Name of the file (e.g., "main.py", "algorithm.cs")
content: Content of the file
Returns:
Dictionary containing file creation result
|
| read_file | Read a specific file from a project or all files if no name provided.
Args:
project_id: ID of the project to read files from
name: Optional name of specific file to read. If not provided, reads all files.
Returns:
Dictionary containing file content(s) or error information
|
| update_file_content | Update the content of a file in a QuantConnect project.
Args:
project_id: ID of the project containing the file
name: Name of the file to update
content: New content for the file
Returns:
Dictionary containing update result
|
| update_file_name | Update the name of a file in a QuantConnect project.
Args:
project_id: ID of the project containing the file
old_file_name: Current name of the file
new_name: New name for the file
Returns:
Dictionary containing update result
|
| create_backtest | Create a new backtest for a compiled project.
Args:
project_id: ID of the project to backtest
compile_id: Compile ID from a successful project compilation
backtest_name: Name for the backtest
parameters: Optional dictionary of parameters for the backtest (e.g., {"ema_fast": 10, "ema_slow": 100})
Returns:
Dictionary containing backtest creation result and backtest details
|
| read_backtest | Read backtest results and statistics from a project.
Args:
project_id: ID of the project containing the backtest
backtest_id: ID of the specific backtest to read
chart: Optional chart name to include chart data in response
Returns:
Dictionary containing backtest results, statistics, and optional chart data
|
| read_backtest_chart | Read chart data from a backtest.
Args:
project_id: Project ID containing the backtest
backtest_id: ID of the backtest to get chart from
name: Name of the chart to retrieve (e.g., "Strategy Equity")
count: Number of data points to request (default: 100)
start: Optional UTC start timestamp in seconds
end: Optional UTC end timestamp in seconds
Returns:
Dictionary containing chart data or loading status
|
| read_backtest_orders | Read orders from a backtest.
Args:
project_id: ID of the project containing the backtest
backtest_id: ID of the backtest to read orders from
start: Starting index of orders to fetch (default: 0)
end: Last index of orders to fetch (default: 100, max range: 100)
Returns:
Dictionary containing orders data and total count
|
| read_backtest_insights | Read insights from a backtest.
Args:
project_id: ID of the project containing the backtest
backtest_id: ID of the backtest to read insights from
start: Starting index of insights to fetch (default: 0)
end: Last index of insights to fetch (default: 100, max range: 100)
Returns:
Dictionary containing insights data and total count
|
| initialize_quantbook | Initialize a new QuantBook instance for research operations.
Args:
instance_name: Name identifier for this QuantBook instance
organization_id: Optional organization ID for QuantConnect
token: Optional API token for QuantConnect
Returns:
Dictionary containing initialization status and instance info
|
| list_quantbook_instances | List all active QuantBook instances.
Returns:
Dictionary containing all active QuantBook instances
|
| get_quantbook_info | Get information about a specific QuantBook instance.
Args:
instance_name: Name of the QuantBook instance
Returns:
Dictionary containing instance information
|
| remove_quantbook_instance | Remove a QuantBook instance from memory.
Args:
instance_name: Name of the QuantBook instance to remove
Returns:
Dictionary containing removal status
|
| add_equity | Add an equity security to the QuantBook instance.
Args:
ticker: Stock ticker symbol (e.g., "AAPL", "SPY")
resolution: Data resolution (Minute, Hour, Daily)
instance_name: QuantBook instance name
Returns:
Dictionary containing the added security information
|
| add_multiple_equities | Add multiple equity securities to the QuantBook instance.
Args:
tickers: List of stock ticker symbols
resolution: Data resolution (Minute, Hour, Daily)
instance_name: QuantBook instance name
Returns:
Dictionary containing results for all added securities
|
| get_history | Retrieve historical data for specified symbols.
Args:
symbols: Single ticker or list of tickers to get history for
start_date: Start date in YYYY-MM-DD format
end_date: End date in YYYY-MM-DD format
resolution: Data resolution (Minute, Hour, Daily)
instance_name: QuantBook instance name
fields: Specific fields to return (open, high, low, close, volume)
Returns:
Dictionary containing historical data
|
| add_alternative_data | Add alternative data source to a security.
Args:
data_type: Type of alternative data (e.g., "SmartInsiderTransaction")
symbol: Symbol to add alternative data for
instance_name: QuantBook instance name
Returns:
Dictionary containing alternative data subscription info
|
| get_alternative_data_history | Retrieve historical alternative data.
Args:
data_type: Type of alternative data
symbols: Symbol(s) to get alternative data for
start_date: Start date in YYYY-MM-DD format
end_date: End date in YYYY-MM-DD format
instance_name: QuantBook instance name
Returns:
Dictionary containing alternative data history
|
| perform_pca_analysis | Perform Principal Component Analysis on historical returns.
Args:
symbols: List of symbols to analyze
start_date: Start date in YYYY-MM-DD format
end_date: End date in YYYY-MM-DD format
n_components: Number of components to compute (default: all)
instance_name: QuantBook instance name
Returns:
Dictionary containing PCA results
|
| test_cointegration | Perform Engle-Granger cointegration test between two assets.
Args:
symbol1: First symbol for cointegration test
symbol2: Second symbol for cointegration test
start_date: Start date in YYYY-MM-DD format
end_date: End date in YYYY-MM-DD format
trend: Trend specification ('c' for constant, 'ct' for constant+trend)
lags: Number of lags to include
instance_name: QuantBook instance name
Returns:
Dictionary containing cointegration test results
|
| analyze_mean_reversion | Analyze mean reversion signals for given symbols.
Args:
symbols: List of symbols to analyze
start_date: Start date in YYYY-MM-DD format
end_date: End date in YYYY-MM-DD format
lookback_period: Lookback period for moving average and std
instance_name: QuantBook instance name
Returns:
Dictionary containing mean reversion analysis results
|
| calculate_correlation_matrix | Calculate correlation matrix for given symbols.
Args:
symbols: List of symbols to analyze
start_date: Start date in YYYY-MM-DD format
end_date: End date in YYYY-MM-DD format
instance_name: QuantBook instance name
Returns:
Dictionary containing correlation matrix and statistics
|
| sparse_optimization | Perform sparse optimization algorithm with Huber Downward Risk minimization.
Args:
portfolio_symbols: List of symbols for the portfolio
benchmark_symbol: Benchmark symbol to track
start_date: Start date in YYYY-MM-DD format
end_date: End date in YYYY-MM-DD format
max_iterations: Maximum iterations for optimization
tolerance: Convergence tolerance
max_weight: Maximum weight per asset
penalty_param: Penalty parameter (p)
huber_param: Huber statistics M-value
lambda_param: Penalty weight (l)
instance_name: QuantBook instance name
Returns:
Dictionary containing optimized portfolio weights and performance
|
| calculate_portfolio_performance | Calculate portfolio performance metrics for given weights.
Args:
symbols: List of portfolio symbols
weights: List of weights corresponding to symbols
start_date: Start date in YYYY-MM-DD format
end_date: End date in YYYY-MM-DD format
benchmark_symbol: Optional benchmark for comparison
instance_name: QuantBook instance name
Returns:
Dictionary containing portfolio performance metrics
|
| optimize_equal_weight_portfolio | Create and analyze an equal-weight portfolio with rebalancing.
Args:
symbols: List of symbols for the portfolio
start_date: Start date in YYYY-MM-DD format
end_date: End date in YYYY-MM-DD format
rebalance_frequency: Rebalancing frequency (daily, weekly, monthly, quarterly)
instance_name: QuantBook instance name
Returns:
Dictionary containing equal-weight portfolio analysis
|
| get_etf_constituents | Get ETF constituents for a specific date using ETF universe data.
Args:
etf_ticker: ETF ticker symbol (e.g., "QQQ", "SPY")
date: Date in YYYY-MM-DD format to get constituents for
instance_name: QuantBook instance name
Returns:
Dictionary containing ETF constituent information
|
| add_etf_universe_securities | Add all ETF constituent securities to the QuantBook instance.
Args:
etf_ticker: ETF ticker symbol
date: Date in YYYY-MM-DD format to get constituents for
resolution: Data resolution (Minute, Hour, Daily)
instance_name: QuantBook instance name
Returns:
Dictionary containing results of adding securities
|
| select_uncorrelated_assets | Select uncorrelated or highly correlated assets from a universe.
Args:
symbols: List of symbols to analyze
start_date: Start date in YYYY-MM-DD format
end_date: End date in YYYY-MM-DD format
num_assets: Number of assets to select
method: Selection method ("lowest_correlation", "highest_correlation")
instance_name: QuantBook instance name
Returns:
Dictionary containing selected assets and correlation analysis
|
| screen_assets_by_criteria | Screen assets based on various performance and risk criteria.
Args:
symbols: List of symbols to screen
start_date: Start date in YYYY-MM-DD format
end_date: End date in YYYY-MM-DD format
min_return: Minimum annualized return threshold
max_volatility: Maximum annualized volatility threshold
min_sharpe: Minimum Sharpe ratio threshold
max_correlation: Maximum correlation with benchmark threshold
benchmark_symbol: Optional benchmark symbol for correlation screening
instance_name: QuantBook instance name
Returns:
Dictionary containing screened assets and their metrics
|