Sequential Thinking Multi-Agent System (MAS)

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This project implements an advanced sequential thinking process using a Multi-Agent System (MAS) built with the Agno framework and served via MCP. It represents a significant evolution from simpler state-tracking approaches by leveraging coordinated, specialized agents for deeper analysis and problem decomposition.

What is This?

This is an MCP server - not a standalone application. It runs as a background service that extends your LLM client (like Claude Desktop) with sophisticated sequential thinking capabilities. The server provides a sequentialthinking tool that processes thoughts through multiple specialized AI agents, each examining the problem from a different cognitive angle.

Core Architecture: Multi-Dimensional Thinking Agents

The system employs 6 specialized thinking agents, each focused on a distinct cognitive perspective:

1. Factual Agent

• Focus: Objective facts and verified data
• Approach: Analytical, evidence-based reasoning
• Capabilities:
  • Web research for current facts (via ExaTools)
  • Data verification and source citation
  • Information gap identification
• Time allocation: 120 seconds for thorough analysis

2. Emotional Agent

• Focus: Intuition and emotional intelligence
• Approach: Gut reactions and feelings
• Capabilities:
  • Quick intuitive responses (30-second snapshots)
  • Visceral reactions without justification
  • Emotional pattern recognition
• Time allocation: 30 seconds (quick reaction mode)

3. Critical Agent

• Focus: Risk assessment and problem identification
• Approach: Logical scrutiny and devil's advocate
• Capabilities:
  • Research counterexamples and failures (via ExaTools)
  • Identify logical flaws and risks
  • Challenge assumptions constructively
• Time allocation: 120 seconds for deep analysis

4. Optimistic Agent

• Focus: Benefits, opportunities, and value
• Approach: Positive exploration with realistic grounding
• Capabilities:
  • Research success stories (via ExaTools)
  • Identify feasible opportunities
  • Explore best-case scenarios logically
• Time allocation: 120 seconds for balanced optimism

5. Creative Agent

• Focus: Innovation and alternative solutions
• Approach: Lateral thinking and idea generation
• Capabilities:
  • Cross-industry innovation research (via ExaTools)
  • Divergent thinking techniques
  • Multiple solution generation
• Time allocation: 240 seconds (creativity needs time)

6. Synthesis Agent

• Focus: Integration and metacognitive orchestration
• Approach: Holistic synthesis and final answer generation
• Capabilities:
  • Integrate all perspectives into coherent response
  • Answer the original question directly
  • Provide actionable, user-friendly insights
• Time allocation: 60 seconds for synthesis
• Note: Uses enhanced model, does NOT include ExaTools (focuses on integration)

AI-Powered Intelligent Routing

The system uses AI-driven complexity analysis to determine the optimal thinking sequence:

Processing Strategy:

• Single fixed strategy

... View full README on GitHub