An integration that exposes TestRail API endpoints to AI assistants for managing test runs, cases, results, and users.

AI-powered Kubernetes management toolkit enabling direct cluster operations, live pod visibility, and YAML-driven workflows. Interacts via natural prompts to list, describe, and modify resources with safe, high-level commands. Designed for seamless integration with Claude Desktop, Cursor, and other AI-assisted clients, it emphasizes safe operations and clear feedback.

Lightweight MCP server that tracks TODOs by file and line, persisting in JSON and integrating with MCP clients.

Lightweight Node.js tool enabling keyword-based text search via a standardized protocol with a client.

A compact MCP server that aggregates Voiceflow and Claude Code documentation for AI assistants. It indexes sources locally, delivers fast full-text search with BM25, and exposes focused tools for finding, retrieving, and exploring content. Ideal for knowledge bases and developer workflows requiring cross-source access.

A toolset that downloads PDFs, chunks content, builds a semantic index, and enables fast PDF search for researchers.

Automates personalized cold outreach by parsing job postings, generating tailored emails with AI, and managing Gmail drafts and sending.

AI-powered organizer analyzes and categorizes screenshots using OCR and vision, enabling fast, automated folder organization

Lightweight TypeScript-based keyword search within files with per-hit line and position data, easily tested via Inspector and adaptable for CI pipelines.

Fetches GitHub data for Rust and Slint, caches locally, and offers six targeted MCP tools.

Browse AI Hub datasets, fetch details, search by keywords, and guide dataset downloads with Claude Desktop integration.

Diverse edge function examples showcasing Hono, mcp-handler, mcp-lite, and SDK patterns with authentication, streaming, and dynamic tool loading on Supabase.

Comprehensive testing and debugging toolkit with smart snapshots, a test client, and safe logging for Model Context Protocol implementations.

AI-powered Bayarcash MCP server enabling guided payments, portal selection, and smart transaction checks with natural language workflows.

Exercise: Integrate Model Context Protocol with GitHub Copilot

Self-contained robotics knowledge hub with offline data, dual HTTP/stdio interfaces, 15+ frameworks, 13+ robot types, 20+ learning resources, and robust tests.

Cloud-native, serverless deployment of MCP functionality to AWS Lambda with auto-scaling and strong security, built on the official Go SDK.

Exercise: Integrate Model Context Protocol with GitHub Copilot

Exercise: Integrate Model Context Protocol with GitHub Copilot

Exercise: Integrate Model Context Protocol with GitHub Copilot

Generic, extensible MCP server enabling context-aware orchestration with pluggable adapters and privacy-preserving negotiation.

Python-based context orchestration with modular plugins, secure sharing, and policy-driven access, enabling dynamic, auditable interactions across agents and tools.

Model context Protocol

Production-grade redaction and compliance tooling with streaming detokenization, policy enforcement, and immutable audit trails.