Multi-Agent Thinking Server

Example Use Cases

• 1

  Explore multiple specialist perspectives (e.g., learning science, data-driven analysis, social learning) in parallel to generate diverse, actionable ideas.

• 2

  Orchestrate and integrate outputs from parallel specialist agents using MCP (FastMCP) to produce a consolidated, multi-faceted solution.

• 3

  A local/on-premises MCP server that integrates with Cursor IDE or Claude Desktop and can call external LLMs via OpenAI and HuggingFace credentials.

Description

This project runs a Multi-Component Protocol (MCP) server that automatically generates and executes specialist agents, each focusing on different approaches or perspectives to solve a given task. It supports multiple problem-solving strategies (e.g., perspective partitioning, task decomposition, parallel solution search) and aggregates specialist reports into final conclusions. Built on HuggingFace's smolagents and FastMCP, it can be invoked as a tool by MCP clients like Cursor IDE and integrated with Claude Desktop.