layer that lets you connect any agent, any tool, any api together.
A framework for building multi-agent AI systems. Enables LLMs to collaborate through hierarchical organization, parallel task execution, and extensible tools.
A technical report / research paper repository for tool integrated reasoning.
Comprehensive guide for building AI tools using Model Context Protocol (MCP). Learn to develop, secure, and deploy production-ready AI integrations.
Agentic framework for dynamic function calling across latest LLMs (gpt-4o, gemini-2.0-flash, groq modes, and anthropic models). Converts Python functions into provider-specific schemas for autonomous tool use. Features unified API, JSON schema generation, and integrated tool execution handling.
AI Assistant with Chainlit Interface A multi-functional AI chatbot built with Chainlit, supporting tools like weather updates, news, jokes, currency exchange, and intelligent agents for writing, email generation, prompt egineering and translation. Users can switch between LLMs like Gemini, Llama, and Exaone, with interactive UI and chat history
This production-ready AI system automates customer support with multi-step workflows, tool integration, stateful conversations, and real-time performance monitoring.
iKOMA – Autonomous local AI assistant with secure internet search, continuous plan-execute-reflect loops, real-time dashboards, and safety-first guardrails.
A Slidev presentation and developer guide to the Model Context Protocol (MCP) by Anthropic, covering AI integration, LLM tool use, core concepts, and implementation examples for AI agents. #mcp #a
This repository delivers end-to-end, code-first tutorials covering every layer of production-grade GenAI agents, guiding you from spark to scale with proven patterns and reusable blueprints for real-world launches.
An end-to-end example demonstrating how to use Model Context Protocol (MCP) over STDIO in .NET to expose server-side tools and consume them from a client, then feed tool results into a local Ollama-hosted LLM for reasoning and response generation.
Tiny Automation Manager
MCP-Agentic AI is an agentic AI framework built around the Model Context Protocol (MCP). It enables modular AI agents to connect to external tools, data sources or services, and orchestrate smart workflows autonomously. The project demonstrates how you can build an AI “agent” that uses MCP servers / tool endpoints.
This project implements a Python LLM-based agent capable of routing user requests to external tools, with a focus on Left-to-Right arithmetic evaluation. The agent CLI integrates tool invocation, JSON-only outputs, and robust expression handling including parentheses and syntax validation.
SynMap generates a syntenic dotplot between two organisms and identifies syntenic regions
LangGraph-powered AI agent with autonomous web search and data retrieval capabilities. Multi-step reasoning system for intelligent information gathering.
A ReAct Chatbot Agent (RAG + Search tool)
AtLoop — agentic task loop for tool-integrated automation.
Project template providing structured initialization for tool integration and configuration.
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