Hello world MCP (Model Context Protocol) project.

Model Context Protocol - Generative AI

Model Context Protocol implementation

Modular query orchestration with context-aware routing and a pluggable LLM backend, combining client, session, and response management.

Lightweight, modular context management and tool integration for AI workflows.

MCP_Model_Context_Protocol_Course

Hands-on experiments exploring context-rich AI workflows with Gemini integration, inspector tooling, and practical notebooks.

Lightweight framework standardizing storage and communication of training config, data lineage, hyperparameters, environment, and deployment metadata in a single archive.

RailTel Model Context Protocol Model

Distributed orchestration delivering integrated product discovery, price comparison, and sentiment-based reviews powered by IBM watsonx.

A full-stack demo showcasing a model-context workflow with SSE transport, Claude integration, and tool calls for guitar recommendations.

Modular MCP server enabling code-aware retrieval and automated README generation with LLM-powered documentation.

Model Context Protocol

Enables Claude AI to write and execute code within Jupyter Notebooks.

Lightweight protocol enabling modular context handling and dynamic tool integration for agentic AI.

Lightweight sentiment analysis with STDIO transport, designed for inspector-based debugging and seamless Python-NPM tooling integration.

用于学习MCP（Model Context Protocol）的仓库

Integrates Google Gemini 2.5 Pro with SerpAPI to enable real-time web search, contextual reasoning, and seamless tool integration for enhanced AI workflows.

LLM Model Context Protocol (MCP) demo using Spring AI

FastAPI-based context processor linking a local Llama model with GitHub repo file listing to enrich queries.

Bridge the Model Context Protocol with Copilot to deliver context-aware code suggestions, share model context across tools, and streamline AI-assisted workflows with lightweight, JavaScript-friendly adapters.

ReAct-style agent demonstrating standardized integration between LLMs and external tools via a universal connector.

Autonomous AI agent system delivering dynamic context retrieval, task decomposition, and secure collaboration to accelerate development workflows.

Provides programmatic AlphaFold predictions, UniProt summaries, and protein annotations via FastMCP for rapid research integration.