Extensible QUADS integration exposing tools, resources, and prompts with flexible config, containerized deployment, and Claude Desktop compatibility.

Lightweight Java Spring-based application exposing an in-memory book catalog to AI tools via a clean protocol, designed for rapid prototyping and effortless tool interoperability.

Lightweight toolkit to explore and prototype Model Context Protocol exchanges, validate messages, and observe context flows.

Lightweight JavaScript-based virtual API for dynamic model context exchange and cross-runtime orchestration.

Modular agent-based RAG chatbot for multi-format documents with traceable, explainable messaging and efficient retrieval.

Intelligent, cached access to CRC/OpenShift Local documentation from multiple sources with smart search and clean text extraction.

Lightweight, city weather retrieval via geocoding and Open-Meteo APIs using a modular TypeScript toolkit.

Go-based file search with resources listing, tool calls, and multi-transport support.

Provides real-time production, performance analytics, health monitoring, and AI-driven maintenance insights for multi-system solar installations.

A unified protocol toolkit for coordinating context-aware models with extensible schemas, enabling scalable, reproducible experiments.

Real-time weather data access via a Model Context Protocol-enabled endpoint with global coverage and async Open-Meteo integration.

A Python-based API offering database-driven model context with semantic queries and contextual data routing.

Lightweight Go implementation enabling real-time context exchange and extensible integration with Minecraft tooling.

Windows-based integration enabling Claude to access FutureVuls vulnerability management: CVEs, tasks, reports, and health checks.

Standardized, portable remote context management enabling seamless cross-runtime collaboration and dynamic prompt handling.

Lightweight, modular patterns with STDIO transport and Gradio integration for rapid experimentation.

Streamlit-based tool that generates personalized learning paths by leveraging context-aware orchestration, integrating YouTube, Drive, and Notion for content, storage, and notes.

Modular Python toolkit delivering safe read-only PostgreSQL access and Bailian-powered AI image generation.

Streamlit-based learning path generator with multi-tool integration for curated, goal-driven plans.

Streamlit-based learning path designer that weaves YouTube, Drive, and Notion via the Model Context Protocol for context-aware, goal-driven study plans.

Lightweight Python implementation of a Thinking Model Context Protocol enabling context-aware reasoning.

Java-based starting point for interoperable model context sharing with pluggable components and extensible MCP routing.

Fast, secure, VS Code-ready PostgreSQL interface with JSON-RPC 2.0 and graceful mock fallback.

This project is a Streamlit-based web application that generates personalized learning paths using the Model Context Protocol (MCP). It integrates with various services including YouTube, Google Drive, and Notion to create comprehensive learning experiences.