AI-powered, multi-exchange signal engine with portfolio optimization and intelligent alerts.

Automates PR analysis with Gemini AI and Slack notifications, featuring templates, webhook-driven workflows, and MCP-powered prompts for streamlined collaboration.

Feature-rich web crawling with JavaScript rendering, AI extraction, YouTube transcripts, and Google search integration for Markdown-ready outputs.

Agent-based RAG chatbot enabling multi-format document QA via MCP with vector retrieval, UI, and detailed logging.

Comprehensive Tavus toolset enabling AI video generation, replica management, conversational AI, lipsync, and speech synthesis with full API v2 coverage.

Ruby gem delivering unified access to multiple LLM providers with session persistence and tool integration.

Gradio-powered transcription tool leveraging Groq Whisper to convert audio and video into text with URL and file support.

Sports-focused context provider offering large-scale QASports QA access through a standardized protocol for rapid, domain-specific LLM guidance.

Comprehensive math computation engine with 34+ tools and a powerful expression evaluator for complex calculations.

Streaming integration for fal.ai models with discovery, schema access, queued and real-time generation, CDN uploads, and HTTP transport for scalable workflows.

This repository complements my Generative AI course, offering essential concepts, code examples, and practical tools. Topics include: Attention & Transformers Deep Learning Foundations Retrieval-Augmented Generation (RAG) Model Context Protocol (MCP) Agentic AI Systems

Versatile context-aware orchestration uniting local Ollama and cloud Groq models with real-time search, memory, and document generation.

Desktop GUI to run local Ollama LLMs and extend with MCP servers for tool calls.

Secure FastAPI-based platform delivering AI-powered data access, semantic search, real-time stock insights, and robust PostgreSQL integration.

Versatile Python MCP client enabling flexible connections, automatic tool execution, and customizable OpenAI endpoints for diverse provider support.

A framework to build and orchestrate OpenAI-powered agents using Model Context Protocol for dynamic context and memory management.

Enterprise-grade RAG for academic documents with OCR processing, multi-model LLM support, hot-reload config, and real-time observability.

Secure, real-time access to trusted salary data within AI chats, delivering percentile insights and auditable match ratings.

Model Context Protocol (MCP) server for Cijene API

A Sample MCP Server for Kubernetes

Lightweight Sequential Thinking MCP Server

🚀 A Model Context Protocol (MCP) server that enables AI assistants to send emails via SMTP. Built with FastMCP and supports Gmail SMTP integration.

A Python-based server implementation of the Model Context Protocol (MCP) designed for Retrieval-Augmented Generation (RAG) workflows. It manages the flow of context, tool invocation and model output in one unified service. Supports modular “Models” and “Modules” directories for extensible integrations, environment configuration, and easy deployment

A Model Context Protocol (MCP) server that demonstrates advanced AI agent capabilities through interactive parameter collection and contextual workflow automation, featuring both official MCP elicitation and intelligent parameter guidance patterns.