mcp-server-mas-sequential-thinking
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This project involves a Multi-Agent System (MAS) implemented in Python using the Agno framework, designed for advanced problem-solving through sequential thinking. It replaces simpler state-tracking approaches by utilizing a coordinated team of specialized agents, thereby enhancing the depth and quality of analysis.
Overview
This project implements a Multi-Agent System (MAS) using the Agno framework and serves it via MCP for complex problem-solving. Key features include:
- Sophisticated tool for sequential thinking in problem-solving with specialized agents like Planner, Researcher, and Synthesizer.
- Active processing, analysis, and synthesis by the agent team.
- Integration with external tools and robust data validation.
- Higher quality of analysis and nuanced thinking through collaborative AI agents.
- Built in Python, leveraging distributed agent logic and specialized roles.
Key Differences from Original Version (TypeScript)
- Transition to a Multi-Agent System from a single class state tracker.
- Active processing logic embedded in agents.
- Utilization of Agno framework and FastMCP for dedicated MAS.
- Structured Python logging and use of Pydantic for data validation.