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A Model Context Protocol (MCP) server implementing the Dual-Cycle Metacognitive Reasoning Framework for autonomous agents. This tool empowers agents with greater self-awareness and reliability through intelligent loop detection and experience acquisition.
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A Model Context Protocol (MCP) server implementation that exposes Pearl's AI and Expert services through a standardized interface
Intelligent Model Context Protocol (MCP) server for AI-assisted API development. Generate mock servers from OpenAPI specs with advanced logging, performance analytics, and server discovery. Optimized for AI development workflows with comprehensive testing insights and automated analysis.
MockLoop MCP is a powerful tool that helps developers create mock API servers effortlessly. 🚀 With just a few commands, you can set up a testing environment that mimics your production API. 💻
pydantic-ai-researcher is a research system that orchestrates an asynchronous loop between two specialized agents: a research agent and an evaluator agent. The research agent answers complex queries using external MCP servers, while the evaluator agent assesses and refines these answers, iterating until a satisfactory response is attained.
A simple chat loop that includes multple mcp servers.