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genpark-quant-concentrated-liquidity-tick-optimizer-skill

genpark-quant-concentrated-liquidity-tick-optimizer-skill

by alphaparkinc
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

genpark-quant-concentrated-liquidity-tick-optimizer-skill

Organization Model Context Protocol Zero-Dependency Python Version Domain License

Production-grade Quantitative Finance & DeFi Microstructure skill engineered strictly with Python standard library. Provides real-time concentrated liquidity optimization, L2 orderbook imbalance metrics, negative-cycle triangular arbitrage detection, and Bayesian Black-Litterman portfolio rebalancing via the Model Context Protocol (MCP).

Architecture & Data Flow

flowchart TD
    MarketFeed[L2 Tick / Orderbook / Exchange Rate Matrix / Covariance] --> Normalizer[Data Normalizer]
    Normalizer --> Core["GenParkQuantConcentratedLiquidityTickOptimizer"]
    Core --> Analytics[Microstructure & Optimization Engine]
    Analytics --> RiskGuard[Slippage & Drawdown Constraints]
    RiskGuard --> MCPOutput[Standard MCP Tool Result / Execution Vector]

Related MCP server: GenPark Quant Orderbook L2 Microstructure Imbalance MCP Server

Quickstart & Usage

1. Direct Python Client Execution

python example_usage.py

2. Standalone MCP Server Launch

Run the native STDIO MCP server:

python mcp_server.py

License

This project is licensed under the MIT License - see the LICENSE file for details.

This server cannot be deployed

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

Resources

Related MCP Connectors

Related MCP Servers

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