deep-thinking-engine
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@deep-thinking-engineHow can we solve climate change effectively?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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
Related MCP server: Clear Thought 1.5
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/ # DocumentationKey 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-validateFor 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.
This server cannot be deployed
Maintenance
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