Model Context Protocol (MCP) for Intelligent Data Analytics Description: In this project, I developed a smart backend architecture called MCP (Model Context Protocol) — a system designed to act as a bridge between natural language user queries and structured data from two databases: MongoDB and MySQL.

SDK-based SwitchBot integration with Cursor: discovers devices, checks status, presses, toggles power, and batch automates with MAC normalization.

Go-based, type-safe, streaming integration toolkit with framework adapters for Gin and Fiber.

End-to-end article drafting system with cross-agent coordination, tool-backed external services, and cloud storage integration for scalable automation.

Modular leave management with apply, balance, and history features, plus personalized greetings and Claude UI option.

MCP (Model Context Protocol) for Microsoft 365. Includes support for Microsoft Graph and other services

C#-based MCP server that executes arbitrary C# scripts using dotnet-script, enabling dynamic code evaluation within MCP workflow.

Real-time Dust agent integration with streaming, full JSON-RPC workflow, secure key handling, and a web test client.

A focused integration delivering fast keyword search and structured Windows API documentation access via stdio for streamlined tooling.

Static quantum code validator with PennyLane support, doc lookup, and version-aware checks.

Python-based MCP server enabling AI-driven automations with Workato, exposing dynamic context sharing and task orchestration.

CLI-integrated workflow enabling robust schema validation, migrations, and code generation for StatelyDB with AI-assisted workflows.

A Model Context Protocol server designed for remote HTTP execution.

A versatile MCP server enabling Claude to trade via Alpaca, combining real-time data, account insights, and natural-language orders.

Quarkus-powered bridge enabling Hyperfoil integration with AI chatbots; lightweight, runnable via jbang, stdio-driven config for easy client-tool compatibility.

Lightweight interface to search Windows binaries, fetch versioned download links, symbol data, and raw metadata with architecture and insider filters.

Exercise: Integrate Model Context Protocol with GitHub Copilot

Exercise: Integrate Model Context Protocol with GitHub Copilot

Bun + TypeScript-based on-chain context provider with configurable chains and rapid local testing for streamlined context workflows.

Modular, plugin-driven microservice enabling contextual AI workflows via a protocol, with secure IPC and extensible adapters.

Lightweight, type-safe Haskell MCP server with extensible adapters and robust async I/O for flexible model-context workflows.

Unified reference harness showcasing prompts, resources, and multi-tool integrations with secure, configurable access, illustrating end-to-end MCP interactions.

FastAPI-based MCP client enabling AI chat with multiple LLMs, tool access, and Docker-ready deployment with OpenAPI docs.

NET-based demo exposing AI tools via stdio transport, auto-loading tools from an assembly, with client-library interactions.