retrieval-augmented-thinking MCP Server

Use This MCP server To

Enable AI models to perform dynamic, multi-step reasoning Manage parallel exploration paths in problem-solving workflows Implement iterative hypothesis testing and validation cycles Preserve context coherence across non-linear reasoning branches Track and revise recursive refinement cycles in thought processes Evaluate reasoning quality in real-time during AI interactions Support adaptive scope adjustment for flexible exploration Integrate structured retrieval-augmented thinking into AI applications

README

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

retrieval-augmented-thinking FAQ

How do I install the retrieval-augmented-thinking MCP server?

Install it via npm using 'npm install @modelcontextprotocol/server-retrieval-augmented-thinking'.

Can this server handle multiple reasoning paths simultaneously?

Yes, it supports branch management for parallel exploration paths.

How does the server maintain context coherence during complex reasoning?

It preserves context across non-linear reasoning paths to ensure coherent thought chains.

Does the server support iterative hypothesis testing?

Yes, it implements validation cycles for iterative hypothesis generation and testing.

Can I track revisions and refinements in reasoning processes?

The server manages recursive refinement cycles and revision tracking effectively.

Is real-time quality assessment of thought processes available?

Yes, it provides real-time evaluation of reasoning quality during interactions.

How flexible is the scope adjustment in reasoning workflows?

The server supports dynamic scope adjustment for flexible exploration and refinement.

What benefits does this server provide over basic retrieval methods?

It enables structured, adaptive, and recursive reasoning beyond simple retrieval, enhancing problem-solving depth.