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
Usage
Command Line
Programmatic Usage
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
Contributing
Contributions welcome! Please read our contributing guidelines and submit pull requests.
License
MIT
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
Usage
Command Line
Programmatic Usage
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
Contributing
Contributions welcome! Please read our contributing guidelines and submit pull requests.
License
MIT