deep-thinking-engine
Enables deep reasoning and cognitive enhancement through multi-agent debate, bias detection, and structured thinking, with privacy-first local execution.
README
MCP Style Agent Collection š§
A collection of local MCP-style agents for cognitive enhancement, deep thinking, and systematic reasoning.
Overview
This project implements multiple specialized MCP (Model Context Protocol) agents that work together to enhance human cognitive capabilities:
š§ Deep Thinking Engine
A comprehensive framework for breaking cognitive limitations through:
- Problem Decomposition: Break complex questions into manageable sub-problems
- Evidence Gathering: Leverage LLM web search for multi-source evidence collection
- Multi-Agent Debate: Organize structured debates from multiple perspectives
- Critical Evaluation: Apply Paul-Elder standards for rigorous thinking assessment
- Bias Detection: Identify and mitigate cognitive biases systematically
- Innovation Methods: Use SCAMPER/TRIZ for breakthrough thinking
- Socratic Reflection: Guide metacognitive awareness and self-assessment
Project Structure
mcp-style-agent/
āāā .kiro/ # Kiro IDE specs and configurations
ā āāā specs/ # Feature specifications
āāā src/ # Source code
ā āāā mcps/ # MCP collection
ā āāā deep_thinking/ # Deep thinking engine
ā āāā shared/ # Shared utilities
āāā tests/ # Test suites
āāā docs/ # Documentation
Key Features
- š Privacy-First: Core reasoning runs locally, only search queries sent externally
- š§ Pluggable Architecture: YAML-configurable thinking flows and custom agents
- š Transparent Process: Complete thinking traces with visualization
- šÆ Scientific Methods: Based on cognitive science and learning research
- ā” Optimized Performance: Intelligent caching and async processing
- šļø Modular Design: Shared components across multiple MCP agents
Quick Start
# Install with uv
uv sync
# Initialize the system
uv run deep-thinking init
# Start a thinking session
uv run deep-thinking think "How can we solve climate change effectively?"
MCP Server Deployment
The Deep Thinking Engine can be deployed as an MCP server for integration with MCP-compatible hosts like Cursor and Claude Desktop.
Using uvx (Recommended)
{
"mcpServers": {
"deep-thinking-engine": {
"command": "uvx",
"args": ["--from", "/path/to/mcp-style-agent", "deep-thinking-mcp-server"],
"env": {
"LOG_LEVEL": "INFO"
}
}
}
}
Test Deployment
# Test uvx deployment
make test-uvx
# Start MCP server locally
make mcp-server
# Validate configuration
make mcp-server-validate
For detailed deployment instructions, see docs/deployment/README.md.
Development
# Setup development environment
uv sync --dev
# Run tests
uv run pytest
# Format code
uv run black .
uv run isort .
Architecture
The system uses a multi-agent architecture with specialized roles:
- Decomposer Agent: Question analysis and breakdown
- Evidence Seeker: Multi-source information gathering
- Debate Orchestrator: Structured multi-perspective analysis
- Critic Agent: Paul-Elder standards evaluation
- Bias Buster: Cognitive bias detection and mitigation
- Innovator Agent: SCAMPER/TRIZ creative thinking
- Reflector Agent: Socratic questioning and metacognition
License
MIT License - see LICENSE file for details.
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