Chain of Draft Server

Example Use Cases

• 1

  Reduce token usage and latency when performing multi-step reasoning with LLMs by using concise intermediate steps.

• 2

  A drop-in MCP-compatible server to integrate Chain of Draft reasoning into Claude/Anthropic-based workflows (including Claude Desktop).

• 3

  Performance analytics and adaptive complexity estimation to choose between concise CoD reasoning and standard CoT when solving domain-specific problems.

Description

This server provides implementations (Python and JavaScript) of the Chain of Draft paradigm, producing minimal yet informative reasoning steps to save tokens and latency while maintaining accuracy. It includes tools for solving math, code, and logic problems, adaptive word-limit enforcement, example transformation from CoT to CoD, and performance analytics. The project is designed for easy integration with Anthropic/Claude (including a Claude Desktop MCP config) and offers analytics and hybrid selection between CoD and CoT based on problem complexity and historical performance.