Discover open-source implementations addressing tool integration & extensible agent servers with autonomous tool loops, retrieval augmented generation, and custom LLM reasoning.
The AI Competitor Intelligence Agent Team is a powerful competitor analysis tool powered by Firecrawl and Agno's AI Agent framework. This app helps businesses analyze their competitors by extracting structured data from competitor...
An advanced AI research agent built using the Agno Agent framework, Together AI's Qwen model, and Composio tools. This agent helps users conduct comprehensive research on any topic by generating research questions, finding answers...
The AI SEO Audit Team is an autonomous, multi-agent workflow built with Google ADK. It takes a webpage URL, crawls the live page, researches real-time SERP competition, and produces a polished, prioritized SEO optimization report.
An advanced web extraction and analysis tool built using Firecrawl's FIRE-1 agent + extract v1 endpoint and the Agno Agent framework to get details of a new startup instantly! This application automatically extracts structured data from...
The AQI Analysis Agent is a powerful air quality monitoring and health recommendation tool powered by Firecrawl and Agno's AI Agent framework. This app helps users make informed decisions about outdoor activities by analyzing real-time...
This app allows you to upload a Resume and a Job Description, then uses an LLM to: A great tool for job seekers to optimize resumes for each application.
A open-source template for building local_ai_legal_agent_team within the Advanced AI Agents category, featuring modular AI integration and clean tool routing.
cd awesome-llm-apps/advancedtoolsframeworks/localchatgptclone 4. Expose the Llama-3 model as an OpenAI API by starting the server in LM Studio.
Demonstrates advanced handoff configuration including callbacks, structured inputs, and custom tool naming. cp ../env.example .env from agent import main.
Demonstrates advanced orchestration patterns where agents are used as tools by other agents. cp ../env.example .env from agents import Runner.
Demonstrates advanced orchestration patterns where specialized agents are used as function tools by orchestrator agents. cp ../env.example .env.
Google ADK provides powerful pre-built tools that are optimized for performance and reliability. These tools integrate seamlessly with Gemini models and provide essential capabilities like web search and code execution.
Demonstrates using OpenAI Agents SDK built-in tools like WebSearchTool and CodeInterpreterTool. cp ../env.example .env from agents import Runner.
This example demonstrates how to connect an ADK agent to a filesystem MCP server using the MCPToolset. The agent can perform file operations like reading, writing, and listing files through the Model Context Protocol.
Welcome to the Firecrawl MCP Agent! This powerful agent demonstrates how to integrate Firecrawl's advanced web scraping capabilities with Google ADK through the Model Context Protocol (MCP).
def calculatecompoundinterest(principal: float, rate: float, years: int) -> dict: Calculate compound interest for an investment. Use this function when users ask about investment growth.
Demonstrates custom function tools creation using the @functiontool decorator. cp ../env.example .env from agents import Runner from agent import rootagent.
A sophisticated multi-agent system built with Google ADK that uses Firecrawl MCP tools for web scraping and coordinates between specialized research and summary agents.
Third-party tools allow you to integrate existing tool ecosystems from frameworks like LangChain, CrewAI, and others. This dramatically expands your agent's capabilities by leveraging battle-tested tools from the broader AI community.
Tools are functions that your agent can call to perform specific tasks. Think of them as the agent's "hands" - they allow the agent to: ┌─────────────────────────────────────────────────────────────┐.
Tool execution callbacks allow you to monitor when agents use tools, track their execution lifecycle, and analyze the results. This provides visibility into how agents interact with external systems and APIs.
Plugins in Google ADK are custom code modules that can be executed at various stages of an agent workflow lifecycle using callback hooks. Unlike regular callbacks that are configured on individual agents or tools, plugins are registered...
AgentScout is an always-on Hacker News briefing agent built with Google ADK. It scans Hacker News for high-signal stories about AI agents, MCP, coding agents, workflow automation, and LLM apps, then turns a featured links into a concise...
A deep research assistant that plans, searches the web, writes to a virtual filesystem, and renders each tool call as a live card in a workspace pane. Built with CopilotKit, Deep Agents, AG-UI, and Tavily on top of Next.js + LangGraph...
Interactive 3D scene renderer using Three.js. Demonstrates streaming code preview and full MCP App integration.
https://github.com/user-attachments/assets/48eeab8d-7845-4d06-83ef-d518a807da03 Book flights, reserve hotels, manage portfolios, and run a kanban board — all inside the chat. Built with CopilotKit, AG-UI, and MCP Apps, showcasing the...
This is an MCP server project bootstrapped with create-mcp-use-app. First, run the development server.
A open-source template for building name within the Generative UI & Frontends category, featuring modular AI integration and clean tool routing.
Reduce LLM API costs by 50-90% through intelligent context compression. Tool outputs are 70-95% redundant boilerplate—Headroom compresses that away while preserving accuracy.
Reduce LLM API costs by 30-60% using TOON (Token-Oriented Object Notation) format for structured data serialization. This app demonstrates how to use Toonify to dramatically reduce token usage when passing structured data to Large...
https://github.com/user-attachments/assets/a01e09fa-131b-479a-8df3-2d1a61fd80f3 A Streamlit application that allows you to browse and interact with websites using natural language commands through the Model Context Protocol (MCP) and...
A Streamlit application that allows you to explore and analyze GitHub repositories using natural language queries through the Model Context Protocol (MCP).
A Streamlit app that demonstrates the multi-agent + MCP pattern: specialized AI agents that each connect to different MCP servers to handle domain-specific tasks.
The Multi-MCP Intelligent Assistant is a powerful productivity tool that integrates multiple Model Context Protocol (MCP) servers to provide seamless access to GitHub, Perplexity, Calendar, and Gmail services through natural language...
A terminal-based Notion Agent for interacting with your Notion pages using natural language through the Notion MCP (Model Context Protocol) server.
Learn how to connect a plain OpenAI function-calling loop to a hosted Streamable HTTP MCP server—without an agent framework. The script keeps the complete bridge visible.
A sophisticated Streamlit-based AI travel planning application that creates extremely detailed, personalized travel itineraries using multiple MCP servers and Google Maps integration. The app uses Airbnb MCP for real accommodation data...
You'll need the following API keys: streamlit run ragreasoningagent.py 4. Configure API Keys:.
The AI Meme Generator Agent is a powerful browser automation tool that creates memes using AI agents. This app combines multi-LLM capabilities with automated browser interactions to generate memes based on text prompts through direct...
The AI Startup Trend Analysis Agent is tool for budding entrepreneurs that generates actionable insights by identifying nascent trends, potential market gaps, and growth opportunities in specific sectors. Entrepreneurs can use these...
