Retrieval-Augmented Thinking MCP Server

An MCP (Model Context Protocol) server implementation that enhances AI model capabilities with structured, retrieval-augmented thinking processes. This server enables dynamic thought chains, parallel exploration paths, and recursive refinement cycles for improved reasoning and problem-solving.

Features

• Adaptive Thought Chains: Maintains coherent reasoning flows with branching and revision capabilities
• Iterative Hypothesis Generation: Implements validation cycles for hypothesis testing
• Context Coherence: Preserves context across non-linear reasoning paths
• Dynamic Scope Adjustment: Supports flexible exploration and refinement
• Quality Assessment: Real-time evaluation of thought processes
• Branch Management: Handles parallel exploration paths
• Revision Tracking: Manages recursive refinement cycles

Installation

npm install @modelcontextprotocol/server-retrieval-augmented-thinking

Usage

Command Line

mcp-server-retrieval-augmented-thinking

Programmatic Usage

import { Server } from '@modelcontextprotocol/sdk/server';
import { StdioServerTransport } from '@modelcontextprotocol/sdk/server/stdio';

// Initialize and run the server
const server = new Server({
  name: 'retrieval-augmented-thinking',
  version: '0.1.0'
});

// Connect transport
const transport = new StdioServerTransport();
await server.connect(transport);

Tool Configuration

The server provides a tool with the following parameters:

• thought (string): Current reasoning step

• thoughtNumber (number): Position in reasoning chain

• totalThoughts (number): Estimated scope

• nextThoughtNeeded (boolean): Chain continuation signal

• isRevision (boolean, optional): Marks refinement steps

• revisesThought (number, optional): References target thought

• branchFromThought (number, optional): Branch origin point

            - `branchId` (string, optional): Branch identifier
  

• needsMoreThoughts (boolean, optional): Scope expansion signal

Advanced Features

Thought Chain Analytics

The server tracks various metrics for thought chain quality:

• Chain effectiveness
• Revision impact
• Branch success rate
• Overall quality
• Individual thought metrics (complexity, depth, quality, impact)

Pattern Recognition

Analyzes thought patterns for:

• Reasoning structures
• Context preservation
• Hypothesis validation
• Solution coherence

Development

# Build
npm run build

# Watch mode
npm run watch

Contributing

Contributions welcome! Please read our contributing guidelines and submit pull requests.

License

MIT