Chain Of Draft Prompt Tool

🚀 MCP Linked List

The MCP (Model Context Protocol) Linked List is a protocol designed for managing model context interactions. Below is a detailed technical documentation for this project.

🚀 Quick Start

The MCP Linked List project is a solution for managing model context interactions. It offers a range of features and tools to support efficient model reasoning and performance monitoring.

✨ Features

• MCP Compatibility: Fully adheres to the MCP protocol specifications.
• Multi - language Support: Available in Python and JavaScript/TypeScript implementations.
• Extensible Plugin System: Allows integration of custom LLM providers and models.
• Performance Monitoring: Comes with built - in analytics tools to track reasoning efficiency.

📦 Installation

MCP Linked List Implementation

To start the MCP Linked List service, you can use the following commands:

# Start the MCP Linked List service
npm run start

# Or run manually
node dist/index.js

This will:

1. Start the MCP server on the default port.
2. Provide full CoD reasoning capabilities.
3. Support interaction with MCP clients.

Python Installation

# Install dependencies
pip install mcp-chain

# Start the service
python -m mcp_chain.server

JavaScript Installation

# Install dependencies
npm install mcp-chain

# Start the service
node src/index.js

💻 Usage Examples

Python Usage Example

# Install dependencies
pip install mcp-chain

# Start the service
python -m mcp_chain.server

JavaScript Usage Example

# Install dependencies
npm install mcp-chain

# Start the service
node src/index.js

📚 Documentation

Core Components

1. MCP Server:
   • Implements the CoD reasoning protocol.
   • Supports multiple problem domains (mathematics, logic, programming, etc.).
   • Provides performance metric collection and reporting functions.
2. LLM Integration:
   • Natively supports mainstream LLM providers such as OpenAI, Anthropic, and Ollama.
   • Supports custom LLM interfaces.
3. Toolset:
   • Includes various reasoning tools, such as problem - solving, mathematical calculation, code analysis, etc.

Toolset

The following is a list of tools provided by the server and their descriptions:

MCP Linked List Monitoring Tool

To start the MCP Linked List monitoring tool, use the following commands:

# Start the monitoring tool
npm run inspect

# Or run manually
node src/monitor.js

This tool provides the following functions:

1. Real - time tracking of reasoning efficiency.
2. Generation of performance reports.
3. Provision of a visualization interface.

🔧 Technical Details

Python Implementation Details

The Python version includes the following core components:

• AnalyticsService: Tracks performance metrics for different domains and reasoning methods.
• ComplexityEstimator: Analyzes problems to determine appropriate word limits.
• ExampleDatabase: Manages and retrieves examples, converting CoT examples to CoD format.
• FormatEnforcer: Ensures reasoning steps comply with word limits.
• ReasoningSelector: Intelligently selects between CoD and CoT based on problem characteristics and historical performance.

JavaScript Implementation Details

The JavaScript version includes the following core components:

• analyticsDb: A database for in - memory tracking of performance metrics.
• complexityEstimator: Analyzes problems to determine complexity and appropriate word limits.
• formatEnforcer: Ensures reasoning steps comply with word limits.
• reasoningSelector: Intelligently selects between CoD and CoT based on problem characteristics and historical performance.

📄 License

This project is licensed under the MIT License, which allows for free modification and distribution. The full license information can be found in the project's LICENSE file.

For more information, please visit the project's official documentation or contact the development team.