Lightweight TypeScript module with pluggable context adapters enabling dynamic, protocol-compliant model interactions.

Lightweight TypeScript todo manager with add, delete, complete, and retrieval operations, designed for local development and easy inspector integration.

A standardized protocol that lets AI understand development context and integrate with tools and GitHub.

Loads CSV-based medical reports, exposes structured questions and answers, with async access and remote retrieval via API.

Strava-connected context enabling AI assistants to securely access and analyze fitness data.

Exercise: Integrate Model Context Protocol with GitHub Copilot

A Model Context Protocol (MCP) server enabling AI assistants to access and manipulate Smartsheet data via a unified API.

Lightweight server for long-lived model contexts with modular storage, pluggable policies, and event-driven updates.

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

Lightweight, dual-mode Perplexity integration with simple env-based configuration and seamless client compatibility.

Exercise: Integrate Model Context Protocol with GitHub Copilot

Bridge Copilot with the Model Context Protocol to deliver richer context-aware code suggestions and streamlined developer workflows.

Implementation of the Model Context Protocol (MCP) framework

Exercise: Integrate Model Context Protocol with GitHub Copilot

Exercise: Integrate Model Context Protocol with GitHub Copilot

Exercise: Integrate Model Context Protocol with GitHub Copilot

Lightweight, extensible framework enabling modular model-context orchestration with pluggable transports and simple integration points.

Type-safe TypeScript SDK enabling seamless integration with context creation and management.

Integrates Veryfi for automated document data extraction with configurable run commands and isolated environments.

NewsAPI-centric integration with modular adapters, real-time updates, and structured metadata for flexible, low-latency news data delivery.

REST-based LLM interface enabling context-aware prompts and structured responses with clear integration points.

Lightweight TypeScript framework for Model Context Protocol integration with pluggable contexts and type-safe messaging.

TypeScript-based Codescan integration providing project listings, metrics, and filtered issues via a unified interface with Docker-ready deployment.

Unified, Python-based tool bridge with a sleek Next.js chat UI for seamless AI-assisted automation.