## 1. Project Overview & Quickstart (ashishpatel26/500-AI-Agents-Projects)

## File: README.md

# 500+ AI Agent Projects & Use Cases



---



## What is this?

A curated collection of **500+ AI agent projects** — production examples, tutorials, and working code spanning every major framework (LangGraph, CrewAI, AutoGen, Agno) and industry (Healthcare, Finance, Education, Cybersecurity, and more).

**Who it's for:**
- 🧑‍💻 **Developers** building their first or next AI agent
- 🔬 **Researchers** surveying the agent landscape
- 🏢 **Teams** evaluating frameworks for production use
- 🎓 **Students** learning agent architectures from real examples

---

## ⚡ Quick Start

Pick a framework and run an agent in under 5 minutes:

```bash
# Clone the repo
git clone https://github.com/ashishpatel26/500-AI-Agents-Projects.git
cd 500-AI-Agents-Projects

# Run any agent from the agents/ directory
cd agents/01-web-research-agent
pip install -r requirements.txt
cp .env.example .env        # add your API key
python agent.py
```

> All agents in `agents/` are self-contained with their own `requirements.txt` and `.env.example`. No monorepo setup needed.

---

## 🗺️ Navigation Guide

| I want to... | Go to |
|---|---|
| Run a working agent right now | [`agents/`](agents/) |
| Browse by AI framework | [Framework-wise Use Cases](#-browse-by-framework) |
| Browse by industry | [Industry Use Cases](#-industry-use-cases) |
| Understand which framework to use | [Framework Comparison](#-framework-comparison) |
| Add my own agent | [Contributing](CONTRIBUTION.md) |
| Learn with a course | [`crewai_mcp_course/`](crewai_mcp_course/) |

---

## 📊 Framework Comparison

Choosing a framework? Here's when to use each:

| Framework | Best For | Complexity | Multi-Agent | Streaming | Local LLM |
|---|---|---|---|---|---|
| **LangGraph** | Stateful workflows, RAG pipelines, complex graphs | ⭐⭐⭐ | ✅ | ✅ | ✅ |
| **CrewAI** | Role-based teams, business automation, rapid prototyping | ⭐⭐ | ✅ | ✅ | ✅ |
| **AutoGen** | Code generation, research, self-healing workflows | ⭐⭐⭐ | ✅ | ✅ | ✅ |
| **Agno** | Lightweight single agents, tool integration, fast iteration | ⭐ | ✅ | ✅ | ✅ |
| **LlamaIndex** | Document Q&A, enterprise RAG, data pipelines | ⭐⭐ | ⚠️ | ✅ | ✅ |

**Quick decision guide:**
- Just starting out → **Agno** or **CrewAI**
- Need stateful graphs + RAG → **LangGraph**
- Building code-writing / research agents → **AutoGen**
- Enterprise document pipelines → **LlamaIndex**

---

## 🏭 Industry Use Cases



| Use Case | Industry | Description | Code |
|---|---|---|---|
| **HIA (Health Insights Agent)** | Healthcare | Analyses medical reports and provides health insights | [](https://github.com/harshhh28/hia) |
| **AI Health Assistant** | Healthcare | Diagnoses and monitors diseases using patient data | [](https://github.com/ahmadvh/AI-Agents-for-Medical-Diagnostics) |
| **Automated Trading Bot** | Finance | Automates stock trading with real-time market analysis | [](https://github.com/MingyuJ666/Stockagent) |
| **Agent Wallet SDK** | Finance | Non-custodial smart contract wallet SDK for AI agents with enforced spend limits | [](https://github.com/up2itnow0822/agent-wallet-sdk) |
| **Virtual AI Tutor** | Education | Provides personalized education tailored to users | [](https://github.com/hqanhh/EduGPT) |
| **24/7 AI Chatbot** | Customer Service | Handles customer queries around the clock | [](https://github.com/NirDiamant/GenAI_Agents/blob/main/all_agents_tutorials/customer_support_agent_langgraph.ipynb) |
| **Product Recommendation Agent** | Retail | Suggests products based on user preferences and history | [](https://github.com/microsoft/RecAI) |
| **Self-Driving Delivery Agent** | Transportation | Optimizes routes and autonomously delivers packages | [](https://github.com/sled-group/driVLMe) |
| **Factory Process Monitoring Agent** | Manufacturing | Monitors production lines and ensures quality control | [](https://github.com/yuchenxia/llm4ias) |
| **Property Pricing Agent** | Real Estate | Analyzes market trends to determine property prices | [](https://github.com/AleksNeStu/ai-real-estate-assistant) |
| **Smart Farming Assistant** | Agriculture | Provides insights on crop health and yield predictions | [](https://github.com/mohammed97ashraf/LLM_Agri_Bot) |
| **Energy Demand Forecasting Agent** | Energy | Predicts energy usage to optimize grid management | [](https://github.com/yecchen/MIRAI) |
| **Content Personalization Agent** | Entertainment | Recommends personalized media based on preferences | [](https://github.com/crosleythomas/MirrorGPT) |
| **Legal Document Review Assistant** | Legal | Automates document review and highlights key clauses | [](https://github.com/firica/legalai) |
| **Recruitment Recommendation Agent** | Human Resources | Suggests best-fit candidates for job openings | [](https://github.com/sentient-engineering/jobber) |
| **Virtual Travel Assistant** | Hospitality | Plans travel itineraries based on preferences | [](https://github.com/nirbar1985/ai-travel-agent) |
| **AI Game Companion Agent** | Gaming | Enhances player experience with real-time assistance | [](https://github.com/onjas-buidl/LLM-agent-game) |
| **Real-Time Threat Detection Agent** | Cybersecurity | Identifies potential threats and mitigates attacks | [](https://github.com/NVISOsecurity/cyber-security-llm-agents) |
| **E-commerce Personal Shopper Agent** | E-commerce | Helps customers find products they'll love | [](https://github.com/Hoanganhvu123/ShoppingGPT) |
| **Logistics Optimization Agent** | Supply Chain | Plans efficient delivery routes and manages inventory | [](https://github.com/microsoft/OptiGuide) |
| **Vibe Hacking Agent** | Cybersecurity | Autonomous Multi-Agent Based Red Team Testing Service | [](https://github.com/PurpleAILAB/Decepticon) |
| **Agent Memory Guard** | Cybersecurity | Detects and blocks memory poisoning attacks (OWASP ASI06) in AI agent memory stores | [](https://github.com/OWASP/www-project-agent-memory-guard) |
| **Citadel** | Software Development | Orchestrates Claude Code agent fleets with lifecycle hooks, skills, campaign management, and postmortem-driven architecture | [](https://github.com/SethGammon/Citadel) |
| **MediSuite-AI-Agent** | Health Insurance | Automates hospital / insurance claiming workflow | [](https://github.com/ahmedmansour5/MediSuite-Ai-Agent) |
| **Lina Egyptian Medical Chatbot** | Healthcare | Egyptian medical assistant chatbot | [](https://github.com/dina-khalid/Lina-Egyptian-Medical-Chatbot) |
| **NextRole (AI Career Assistant)** | Human Resources | Tailors a resume to a job description and generates interview prep plus a day-of battlecard via a multi-agent system | [](https://github.com/tam159/next-role) |
| **PII Sanitization Agent** | Privacy/Compliance | Redacts PII (emails, phones, national IDs, bank accounts, API keys) from text before it reaches an LLM; fail-closed, multilingual, on-chain proof via TrustBoost | [](https://github.com/teodorofodocrispin-cmyk/TrustBoost-PII-Sanitizer) |

---

## 🔧 Browse by Framework

### CrewAI

Role-based multi-agent framework. Great for business automation.

| Use Case | Industry | Description | GitHub |
|---|---|---|---|
| 📧 Email Auto Responder Flow | Communication | Automates email responses based on predefined criteria | [](https://github.com/crewAIInc/crewAI-examples/tree/main/flows/email_auto_responder_flow) |
| 📝 Meeting Assistant Flow | Productivity | Organizes meetings, scheduling and agenda preparation | [](https://github.com/crewAIInc/crewAI-examples/tree/main/flows/meeting_assistant_flow) |
| 🔄 Self Evaluation Loop Flow | Human Resources | Facilitates self-assessment for performance reviews | [](https://github.com/crewAIInc/crewAI-examples/tree/main/flows/self_evaluation_loop_flow) |
| 📈 Lead Score Flow | Sales | Evaluates and scores potential leads to prioritize outreach | [](https://github.com/crewAIInc/crewAI-examples/tree/main/flows/lead-score-flow) |
| 📊 Marketing Strategy Generator | Marketing | Develops marketing strategies by analyzing market trends | [](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/marketing_strategy) |
| 📝 Job Posting Generator | Recruitment | Creates job postings by analyzing job requirements | [](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/job-posting) |
| 🔄 Recruitment Workflow | Recruitment | Streamlines recruitment by automating hiring tasks | [](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/recruitment) |
| 🔍 Match Profile to Positions | Recruitment | Matches candidate profiles to suitable job positions | [](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/match_profile_to_positions) |
| 📸 Instagram Post Generator | Social Media | Generates and schedules Instagram posts automatically | [](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/instagram_post) |
| 🌐 Landing Page Generator | Web Development | Automates creation of landing pages for websites | [](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/landing_page_generator) |
| 🎮 Game Builder Crew | Game Development | Assists in game development by automating aspects of creation | [](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/game-builder-crew) |
| 💹 Stock Analysis Tool | Finance | Provides tools for analyzing stock market data | [](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/stock_analysis) |
| 🗺️ Trip Planner | Travel | Assists in planning trips with itineraries | [](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/trip_planner) |
| 🎁 Surprise Trip Planner | Travel | Plans surprise trips based on user preferences | [](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/surprise_trip) |
| 📚 Write a Book with Flows | Creative Writing | Assists authors with structured writing workflows | [](https://github.com/crewAIInc/crewAI-examples/tree/main/flows/write_a_book_with_flows) |
| 🎬 Screenplay Writer | Creative Writing | Aids in writing screenplays with templates and guidance | [](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/screenplay_writer) |
| ✅ Markdown Validator | Documentation | Validates Markdown files for proper formatting | [](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/markdown_validator) |
| 🧠 Meta Quest Knowledge | Knowledge Management | Manages Meta Quest knowledge for information retrieval | [](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/meta_quest_knowledge) |
| 🤖 NVIDIA Models Integration | AI Integration | Integrates NVIDIA AI models into workflows | [](https://github.com/crewAIInc/crewAI-examples/tree/main/integrations/nvidia_models) |
| 🗂️ Prep for a Meeting | Productivity | Prepares meeting materials and sets agendas | [](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/prep-for-a-meeting) |
| 🛠️ Starter Template | Development | Starter template for new CrewAI projects | [](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/starter_template) |
| 🔗 CrewAI + LangGraph Integration | AI Integration | Integration between CrewAI and LangGraph | [](https://github.com/crewAIInc/crewAI-examples/tree/main/integrations/CrewAI-LangGraph) |

---

### AutoGen

Microsoft's framework for code generation, execution, and multi-agent research.

**Code Generation, Execution, and Debugging**

| Use Case | Industry | Description | Notebook |
|---|---|---|---|
| 🤖 Automated Task Solving with Code Gen, Execution & Debugging | Software Development | Demonstrates automated task-solving by generating, executing, and debugging code | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_auto_feedback_from_code_execution) |
| 🧑‍💻 Code Generation and Q&A with Retrieval Augmented Agents | Software Development | Generates code and answers questions using retrieval-augmented methods | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_RetrieveChat) |
| 🧠 Code Generation and Q&A with Qdrant-based Retrieval | Software Development | Utilizes Qdrant for enhanced retrieval-augmented agent performance | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_RetrieveChat_qdrant) |

**Multi-Agent Collaboration**

| Use Case | Industry | Description | Notebook |
|---|---|---|---|
| 🤝 Group Chat (3 members, 1 manager) | Collaboration | Demonstrates group task-solving via multi-agent collaboration | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_groupchat) |
| 📊 Data Visualization by Group Chat | Data Analysis | Uses multi-agent collaboration to create data visualizations | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_groupchat_vis) |
| 🧩 Complex Task Solving by Group Chat (6 members) | Collaboration | Solves complex tasks collaboratively with a larger group | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_groupchat_research) |
| 🧑‍💻 Task Solving with Coding & Planning Agents | Planning & Dev | Combines coding and planning agents for solving tasks | [](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_planning.ipynb) |
| 📐 Task Solving with Graph Transition Paths | Collaboration | Uses predefined transition paths in a graph for solving tasks | [](https://microsoft.github.io/autogen/docs/notebooks/agentchat_groupchat_finite_state_machine) |
| 🧠 SocietyOfMindAgent Inner-Monologue | Cognitive Sciences | Simulates inner-monologue for problem-solving using group chats | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_society_of_mind) |
| 🔧 Group Chat with Custom Speaker Selection | Collaboration | Implements a custom function for speaker selection | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_groupchat_customized) |

**Sequential Multi-Agent Chats**

| Use Case | Industry | Description | Notebook |
|---|---|---|---|
| 🔄 Sequential Task-Solving (single initiating agent) | Workflow Automation | Automates sequential task-solving with a single initiating agent | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_multi_task_chats) |
| ⏳ Async Sequential Task-Solving | Workflow Automation | Handles asynchronous task-solving in a sequence of chats | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_multi_task_async_chats) |
| 🤝 Sequential Chats with Different Initiating Agents | Workflow Automation | Sequential task-solving with different agents initiating each chat | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchats_sequential_chats) |

**Nested Chats**

| Use Case | Industry | Description | Notebook |
|---|---|---|---|
| 🧠 Solving Complex Tasks with Nested Chats | Problem Solving | Uses nested chats to solve hierarchical and complex problems | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_nestedchat) |
| 🔄 Sequence of Nested Chats | Problem Solving | Demonstrates sequential task-solving using nested chats | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_nested_sequential_chats) |
| 🏭 OptiGuide Supply Chain with Nested Chats | Supply Chain | Solves supply chain optimization using nested chats | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_nestedchat_optiguide) |
| ♟️ Conversational Chess with Nested Chats | Gaming | Uses nested chats for playing conversational chess with tools | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_nested_chats_chess) |

**Tools**

| Use Case | Industry | Description | Notebook |
|---|---|---|---|
| 🌐 Web Search: Solve Tasks Requiring Web Info | Information Retrieval | Searches the web to gather information for completing tasks | [](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_web_info.ipynb) |
| 🔧 Use Provided Tools as Functions | Tool Integration | Demonstrates how to use pre-provided tools as callable functions | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_function_call_currency_calculator) |
| 📚 RAG Group Chat | Collaboration | Enables group chat with Retrieval Augmented Generation | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_groupchat_RAG) |
| 🔊 Agent Chat with Whisper | Audio Processing | AI agent for transcription and translation using Whisper | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_video_transcript_translate_with_whisper) |
| 📊 SQL: Natural Language to SQL Query | Database Management | Converts natural language inputs into SQL queries | [](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_sql_spider.ipynb) |

**Multimodal Agents**

| Use Case | Industry | Description | Notebook |
|---|---|---|---|
| 🎨 Multimodal Agent with DALLE and GPT-4V | Multimedia AI | Combines DALLE and GPT-4V for multimodal agent communication | [](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_dalle_and_gpt4v.ipynb) |
| 🖌️ Multimodal Agent with Llava | Image Processing | Uses Llava for multimodal agent conversations | [](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_lmm_llava.ipynb) |
| 🖼️ Multimodal Agent with GPT-4V | Multimedia AI | Leverages GPT-4V for visual and conversational interactions | [](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_lmm_gpt-4v.ipynb) |

**Observability & Evaluation**

| Use Case | Industry | Description | Notebook |
|---|---|---|---|
| 📊 AgentEval: Multi-Agent Assessment System | Performance Evaluation | Evaluating LLM-based application utility | [](https://github.com/microsoft/autogen/blob/0.2/notebook/agenteval_cq_math.ipynb) |
| 📊 Track LLM Calls and Errors using AgentOps | Monitoring & Analytics | Monitors LLM interactions, tool usage, and errors | [](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_agentops.ipynb) |
| 🏗️ Auto Build Multi-agent System with AgentBuilder | AI Development | Automatically builds multi-agent systems | [](https://github.com/microsoft/autogen/blob/0.2/notebook/autobuild_basic.ipynb) |

---

### Agno

Lightweight, fast agent framework. Best for single-agent tools and rapid prototyping.

| Use Case | Industry | Description | Code |
|---|---|---|---|
| 🤖 Support Agent | AI Framework Support | Real-time answers, explanations, and code examples for Agno framework | [](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/agno_support_agent.py) |
| 🎥 YouTube Agent | Media & Content | Analyzes YouTube videos: summaries, timestamps, themes | [](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/youtube_agent.py) |
| 📊 Finance Agent (Thinking) | Finance | Real-time stock insights, analyst recommendations, financial deep-dives | [](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/thinking_finance_agent.py) |
| 📚 Study Partner | Education | Finds resources, answers questions, creates study plans | [](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/study_partner.py) |
| 🛍️ Shopping Partner Agent | E-commerce | Product recommender based on preferences from Amazon, Flipkart | [](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/shopping_partner.py) |
| 🎓 Research Scholar Agent | Education / Research | Advanced academic searches, publication analysis, structured reports | [](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/research_agent_exa.py) |
| 🧠 Research Agent | Media & Journalism | Deep investigations, NYT-style reports | [](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/research_agent.py) |
| 🍳 Recipe Creator | Food & Culinary | Personalized recipes based on ingredients and preferences | [](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/recipe_creator.py) |
| 🧠 Financial Reasoning Agent | Finance | Claude 3.5 Sonnet-based stock analysis with Yahoo Finance data | [](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/reasoning_finance_agent.py) |
| 🤖 Readme Generator Agent | Software Dev | Generates high-quality READMEs for GitHub repos | [](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/readme_generator.py) |
| 🎬 Movie Recommendation Agent | Entertainment | Personalized movie recommendations using Exa and GPT-4o | [](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/movie_recommedation.py) |
| 🔍 Media Trend Analysis Agent | Media & News | Analyzes emerging trends and influencers from digital platforms | [](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/media_trend_analysis_agent.py) |
| ⚖️ Legal Document Analysis Agent | Legal Tech | Analyzes legal PDFs and provides insights using vector embeddings | [](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/legal_consultant.py) |
| 🤔 DeepKnowledge | Research | Iterative search through knowledge base with deep reasoning | [](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/deep_knowledge.py) |
| 📚 Book Recommendation Agent | Publishing & Media | Personalized book suggestions using literary data and reader preferences | [](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/book_recommendation.py) |
| 🏠 MCP Airbnb Agent | Hospitality | Search Airbnb listings with MCP and Llama 4 | [](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/airbnb_mcp.py) |
| 🤖 Agno Assist Agent | AI Framework | GPT-4o agent for Agno framework Q&A with hybrid search | [](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/agno_assist.py) |

---

### LangGraph

State-machine framework for complex, stateful agent workflows and RAG pipelines.

| Use Case | Industry | Description | Code |
|---|---|---|---|
| 🤖 Chatbot Simulation Evaluation | AI / QA | Simulate user interactions to evaluate chatbot performance | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/chatbot-simulation-evaluation/agent-simulation-evaluation.ipynb) |
| 🧠 Information Gathering via Prompting | Research | LangGraph workflow using prompting to gather information | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/chatbots/information-gather-prompting.ipynb) |
| 🧠 Code Assistant with LangGraph | Software Development | Resilient code assistant with error checking and iterative refinement | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/code_assistant/langgraph_code_assistant.ipynb) |
| 🧑‍💼 Customer Support Agent | Customer Support | Graph-based agent for handling customer inquiries | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/customer-support/customer-support.ipynb) |
| 🔁 Extraction with Retries | Data Extraction | Retry mechanisms for robust data extraction | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/extraction/retries.ipynb) |
| 🧠 Multi-Agent Workflow (Supervisor) | Workflow Orchestration | Supervisor agent orchestrating multiple specialized agents | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/multi_agent/agent_supervisor.ipynb) |
| 🧠 Hierarchical Agent Teams | Workflow Orchestration | Top-level supervisor delegates to specialized sub-agents | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/multi_agent/hierarchical_agent_teams.ipynb) |
| 🤝 Multi-Agent Collaboration | Workflow Orchestration | Multiple specialized agents working together on complex tasks | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/multi_agent/multi-agent-collaboration.ipynb) |
| 🧠 Plan-and-Execute Agent | Workflow Orchestration | Agent generates multi-step plan then executes sequentially | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/plan-and-execute/plan-and-execute.ipynb) |
| 🧠 SQL Agent | Database Interaction | Agent answers questions about SQL databases | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/sql-agent.ipynb) |
| 🧠 Reflection Agent | Workflow Orchestration | Agent critiques and revises its own outputs | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/reflection/reflection.ipynb) |
| 🧠 Reflexion Agent | Workflow Orchestration | Agent reflects on actions for iterative improvement | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/reflexion/reflexion.ipynb) |
| 🧠 Adaptive RAG | Information Retrieval | Dynamic retrieval adjusting based on query complexity | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/rag/langgraph_adaptive_rag.ipynb) |
| 🤖 Agentic RAG | Intelligent Agents | Agent determines best retrieval strategy before generating response | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/rag/langgraph_agentic_rag.ipynb) |
| 🧠 Corrective RAG (CRAG) | Information Retrieval | Evaluates and refines retrieved documents before generation | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/rag/langgraph_crag.ipynb) |
| 🧠 Self-RAG | Information Retrieval | System reflects on responses and retrieves additional info if needed | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/rag/langgraph_self_rag.ipynb) |
| 🧠 Adaptive RAG (Local) | Information Retrieval | Adaptive RAG with local models for offline use | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/rag/langgraph_adaptive_rag_local.ipynb) |
| 🧠 Self-RAG (Local) | Information Retrieval | Self-RAG using local models and data sources | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/rag/langgraph_self_rag_local.ipynb) |

---

## 🤝 Contributing

Contributions are welcome! 🎉 This repo grows through community contributions.

**Ways to contribute:**
1. **Add a working agent** — create a folder in `agents/` with runnable code
2. **Add an external link** — add a row to the industry or framework tables
3. **Fix a broken link** — open an issue or PR
4. **Improve documentation** — fix typos, add context, improve examples

**To contribute:**
1. Fork the repository
2. Create a branch: `feat/agent-name` or `fix/description`
3. Add your changes following the [Contributing Guidelines](CONTRIBUTION.md)
4. Open a PR using the PR template

See [CONTRIBUTION.md](CONTRIBUTION.md) for full requirements (metadata.yaml, requirements.txt, etc.).

---

## Star History

[](https://star-history.com/#ashishpatel26/500-AI-Agents-Projects&Date)

<sub>Regenerated weekly from the GitHub API by [`.github/workflows/star-history.yml`](.github/workflows/star-history.yml). Click the chart for the interactive version.</sub>

---

## 📜 License

This repository is licensed under the MIT License. See the [LICENSE](LICENSE) file for more information.

---

---

## File: crewai_mcp_course/README.md

# CrewAI with FastMCP Server Integration Course

This course teaches beginners how to use CrewAI with FastMCP server access through step-by-step programming examples.

## Course Overview

This course is designed for beginner developers with basic Python knowledge who want to learn how to integrate CrewAI agents with FastMCP servers. The course covers fundamental concepts, practical implementation, and advanced patterns for building intelligent agent workflows.

## Lessons

### Lesson 1: Setting up CrewAI with MCP Server Access
- Install required packages
- Set up environment variables
- Create a basic CrewAI agent
- Execute simple tasks

```mermaid
graph TD
    A[Install Packages] --> B[Set Environment Variables]
    B --> C[Create CrewAI Agent]
    C --> D[Execute Task]
```

### Lesson 2: Integrating MCP Server with CrewAI
- Create custom tools for MCP server access
- Configure authentication and connection settings
- Use MCP server data in agent tasks
- Handle errors and exceptions

```mermaid
graph TD
    A[Create FastMCP Tool] --> B[Configure Authentication]
    B --> C[Create Agent with Tool]
    C --> D[Execute Task with MCP Data]
    D --> E[Handle Response]
```

### Lesson 3: Advanced CrewAI Patterns with MCP Server
- Implement multi-agent workflows
- Use hierarchical processes
- Share data between agents through the MCP server
- Store and retrieve research findings
- Implement quality assurance processes

```mermaid
graph TD
    A[Researcher Agent] -->|Query| B(FastMCP Server)
    B -->|Return Data| A
    A -->|Share Findings| C[Writer Agent]
    C -->|Create Report| D[Reviewer Agent]
    D -->|Provide Feedback| C
    C -->|Final Report| E[Output]
```

## Getting Started

### Using pip (traditional method)

1. Install the required packages for the lesson you want to run:
```bash
pip install -r lesson_01/requirements.txt
pip install -r lesson_02/requirements.txt
pip install -r lesson_03/requirements.txt
```

2. Set up your environment variables:
```bash
export OPENAI_API_KEY=your-openai-api-key
export MCP_SERVER_URL=http://localhost:8000
```

3. Run the examples:
```bash
python lesson_01/agent.py
python lesson_02/agent.py --topic "AI agents in healthcare"

# Lesson 03 includes a matching FastMCP server and CrewAI wrappers.
python lesson_03/agent.py
# Optional: inspect/run the FastMCP server separately:
python lesson_03/mcp_server.py
```

### Using uv (recommended modern method)

[uv](https://github.com/astral-sh/uv) is a fast Python package installer and resolver. To use uv:

1. Install uv:
```bash
pip install uv
```

2. Create and activate a virtual environment:
```bash
uv venv
source .venv/Scripts/activate
```

3. Install dependencies:
```bash
uv pip install -r lesson_01/requirements.txt
uv pip install -r lesson_02/requirements.txt
uv pip install -r lesson_03/requirements.txt
```

4. Set up your environment variables:
```bash
export OPENAI_API_KEY=your-openai-api-key
export MCP_SERVER_URL=http://localhost:8000
```

5. Run the examples:
```bash
python lesson_01/agent.py
python lesson_02/agent.py --topic "AI agents in healthcare"

python lesson_03/agent.py
# Optional: inspect/run the FastMCP server separately:
python lesson_03/mcp_server.py
```

## Requirements

- Python 3.8+
- CrewAI library
- FastMCP library
- OpenAI API key
- FastMCP server example for Lesson 03

## Course Structure

Each lesson includes:
- A lesson folder with `agent.py`, `requirements.txt`, and `.env.example`
- Clear objectives and expected outcomes
- Step-by-step implementation
- Best practices for error handling and security

## Next Steps

After completing this course, you should be able to:
- Create and configure CrewAI agents
- Integrate MCP servers with agent workflows
- Build complex multi-agent systems
- Implement data sharing between agents
- Design robust error handling for production systems

## 2. Official Technical Reference & Guides (ashishpatel26/ashishpatel26.github.io)

# 500+ AI Agent Projects & Use Cases



---



## What is this?

A curated collection of **500+ AI agent projects** — production examples, tutorials, and working code spanning every major framework (LangGraph, CrewAI, AutoGen, Agno) and industry (Healthcare, Finance, Education, Cybersecurity, and more).

**Who it's for:**
- 🧑‍💻 **Developers** building their first or next AI agent
- 🔬 **Researchers** surveying the agent landscape
- 🏢 **Teams** evaluating frameworks for production use
- 🎓 **Students** learning agent architectures from real examples

---

## ⚡ Quick Start

Pick a framework and run an agent in under 5 minutes:

```bash
# Clone the repo
git clone https://github.com/ashishpatel26/500-AI-Agents-Projects.git
cd 500-AI-Agents-Projects

# Run any agent from the agents/ directory
cd agents/01-web-research-agent
pip install -r requirements.txt
cp .env.example .env        # add your API key
python agent.py
```

> All agents in `agents/` are self-contained with their own `requirements.txt` and `.env.example`. No monorepo setup needed.

---

## 🗺️ Navigation Guide

| I want to... | Go to |
|---|---|
| Run a working agent right now | [`agents/`](agents/) |
| Browse by AI framework | [Framework-wise Use Cases](#-browse-by-framework) |
| Browse by industry | [Industry Use Cases](#-industry-use-cases) |
| Understand which framework to use | [Framework Comparison](#-framework-comparison) |
| Add my own agent | [Contributing](CONTRIBUTION.md) |
| Learn with a course | [`crewai_mcp_course/`](crewai_mcp_course/) |

---

## 📊 Framework Comparison

Choosing a framework? Here's when to use each:

| Framework | Best For | Complexity | Multi-Agent | Streaming | Local LLM |
|---|---|---|---|---|---|
| **LangGraph** | Stateful workflows, RAG pipelines, complex graphs | ⭐⭐⭐ | ✅ | ✅ | ✅ |
| **CrewAI** | Role-based teams, business automation, rapid prototyping | ⭐⭐ | ✅ | ✅ | ✅ |
| **AutoGen** | Code generation, research, self-healing workflows | ⭐⭐⭐ | ✅ | ✅ | ✅ |
| **Agno** | Lightweight single agents, tool integration, fast iteration | ⭐ | ✅ | ✅ | ✅ |
| **LlamaIndex** | Document Q&A, enterprise RAG, data pipelines | ⭐⭐ | ⚠️ | ✅ | ✅ |

**Quick decision guide:**
- Just starting out → **Agno** or **CrewAI**
- Need stateful graphs + RAG → **LangGraph**
- Building code-writing / research agents → **AutoGen**
- Enterprise document pipelines → **LlamaIndex**

---

## 🏭 Industry Use Cases



| Use Case | Industry | Description | Code |
|---|---|---|---|
| **HIA (Health Insights Agent)** | Healthcare | Analyses medical reports and provides health insights | [](https://github.com/harshhh28/hia.git) |
| **AI Health Assistant** | Healthcare | Diagnoses and monitors diseases using patient data | [](https://github.com/ahmadvh/AI-Agents-for-Medical-Diagnostics.git) |
| **Automated Trading Bot** | Finance | Automates stock trading with real-time market analysis | [](https://github.com/MingyuJ666/Stockagent.git) |
| **Agent Wallet SDK** | Finance | Non-custodial smart contract wallet SDK for AI agents with enforced spend limits | [](https://github.com/up2itnow0822/agent-wallet-sdk) |
| **Virtual AI Tutor** | Education | Provides personalized education tailored to users | [](https://github.com/hqanhh/EduGPT.git) |
| **24/7 AI Chatbot** | Customer Service | Handles customer queries around the clock | [](https://github.com/NirDiamant/GenAI_Agents/blob/main/all_agents_tutorials/customer_support_agent_langgraph.ipynb) |
| **Product Recommendation Agent** | Retail | Suggests products based on user preferences and history | [](https://github.com/microsoft/RecAI) |
| **Self-Driving Delivery Agent** | Transportation | Optimizes routes and autonomously delivers packages | [](https://github.com/sled-group/driVLMe) |
| **Factory Process Monitoring Agent** | Manufacturing | Monitors production lines and ensures quality control | [](https://github.com/yuchenxia/llm4ias) |
| **Property Pricing Agent** | Real Estate | Analyzes market trends to determine property prices | [](https://github.com/AleksNeStu/ai-real-estate-assistant) |
| **Smart Farming Assistant** | Agriculture | Provides insights on crop health and yield predictions | [](https://github.com/mohammed97ashraf/LLM_Agri_Bot) |
| **Energy Demand Forecasting Agent** | Energy | Predicts energy usage to optimize grid management | [](https://github.com/yecchen/MIRAI) |
| **Content Personalization Agent** | Entertainment | Recommends personalized media based on preferences | [](https://github.com/crosleythomas/MirrorGPT) |
| **Legal Document Review Assistant** | Legal | Automates document review and highlights key clauses | [](https://github.com/firica/legalai) |
| **Recruitment Recommendation Agent** | Human Resources | Suggests best-fit candidates for job openings | [](https://github.com/sentient-engineering/jobber) |
| **Virtual Travel Assistant** | Hospitality | Plans travel itineraries based on preferences | [](https://github.com/nirbar1985/ai-travel-agent) |
| **AI Game Companion Agent** | Gaming | Enhances player experience with real-time assistance | [](https://github.com/onjas-buidl/LLM-agent-game) |
| **Real-Time Threat Detection Agent** | Cybersecurity | Identifies potential threats and mitigates attacks | [](https://github.com/NVISOsecurity/cyber-security-llm-agents) |
| **E-commerce Personal Shopper Agent** | E-commerce | Helps customers find products they'll love | [](https://github.com/Hoanganhvu123/ShoppingGPT) |
| **Logistics Optimization Agent** | Supply Chain | Plans efficient delivery routes and manages inventory | [](https://github.com/microsoft/OptiGuide) |
| **Vibe Hacking Agent** | Cybersecurity | Autonomous Multi-Agent Based Red Team Testing Service | [](https://github.com/PurpleAILAB/Decepticon) |
| **Citadel** | Software Development | Orchestrates Claude Code agent fleets with lifecycle hooks, skills, campaign management, and postmortem-driven architecture | [](https://github.com/SethGammon/Citadel) |
| **MediSuite-AI-Agent** | Health Insurance | Automates hospital / insurance claiming workflow | [](https://github.com/ahmedmansour5/MediSuite-Ai-Agent) |
| **Lina Egyptian Medical Chatbot** | Healthcare | Egyptian medical assistant chatbot | [](https://github.com/dina-khalid/Lina-Egyptian-Medical-Chatbot) |

---

## 🔧 Browse by Framework

### CrewAI

Role-based multi-agent framework. Great for business automation.

| Use Case | Industry | Description | GitHub |
|---|---|---|---|
| 📧 Email Auto Responder Flow | Communication | Automates email responses based on predefined criteria | [](https://github.com/crewAIInc/crewAI-examples/tree/main/flows/email_auto_responder_flow) |
| 📝 Meeting Assistant Flow | Productivity | Organizes meetings, scheduling and agenda preparation | [](https://github.com/crewAIInc/crewAI-examples/tree/main/flows/meeting_assistant_flow) |
| 🔄 Self Evaluation Loop Flow | Human Resources | Facilitates self-assessment for performance reviews | [](https://github.com/crewAIInc/crewAI-examples/tree/main/flows/self_evaluation_loop_flow) |
| 📈 Lead Score Flow | Sales | Evaluates and scores potential leads to prioritize outreach | [](https://github.com/crewAIInc/crewAI-examples/tree/main/flows/lead-score-flow) |
| 📊 Marketing Strategy Generator | Marketing | Develops marketing strategies by analyzing market trends | [](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/marketing_strategy) |
| 📝 Job Posting Generator | Recruitment | Creates job postings by analyzing job requirements | [](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/job-posting) |
| 🔄 Recruitment Workflow | Recruitment | Streamlines recruitment by automating hiring tasks | [](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/recruitment) |
| 🔍 Match Profile to Positions | Recruitment | Matches candidate profiles to suitable job positions | [](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/match_profile_to_positions) |
| 📸 Instagram Post Generator | Social Media | Generates and schedules Instagram posts automatically | [](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/instagram_post) |
| 🌐 Landing Page Generator | Web Development | Automates creation of landing pages for websites | [](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/landing_page_generator) |
| 🎮 Game Builder Crew | Game Development | Assists in game development by automating aspects of creation | [](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/game-builder-crew) |
| 💹 Stock Analysis Tool | Finance | Provides tools for analyzing stock market data | [](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/stock_analysis) |
| 🗺️ Trip Planner | Travel | Assists in planning trips with itineraries | [](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/trip_planner) |
| 🎁 Surprise Trip Planner | Travel | Plans surprise trips based on user preferences | [](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/surprise_trip) |
| 📚 Write a Book with Flows | Creative Writing | Assists authors with structured writing workflows | [](https://github.com/crewAIInc/crewAI-examples/tree/main/flows/write_a_book_with_flows) |
| 🎬 Screenplay Writer | Creative Writing | Aids in writing screenplays with templates and guidance | [](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/screenplay_writer) |
| ✅ Markdown Validator | Documentation | Validates Markdown files for proper formatting | [](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/markdown_validator) |
| 🧠 Meta Quest Knowledge | Knowledge Management | Manages Meta Quest knowledge for information retrieval | [](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/meta_quest_knowledge) |
| 🤖 NVIDIA Models Integration | AI Integration | Integrates NVIDIA AI models into workflows | [](https://github.com/crewAIInc/crewAI-examples/tree/main/integrations/nvidia_models) |
| 🗂️ Prep for a Meeting | Productivity | Prepares meeting materials and sets agendas | [](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/prep-for-a-meeting) |
| 🛠️ Starter Template | Development | Starter template for new CrewAI projects | [](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/starter_template) |
| 🔗 CrewAI + LangGraph Integration | AI Integration | Integration between CrewAI and LangGraph | [](https://github.com/crewAIInc/crewAI-examples/tree/main/integrations/CrewAI-LangGraph) |

---

### AutoGen

Microsoft's framework for code generation, execution, and multi-agent research.

**Code Generation, Execution, and Debugging**

| Use Case | Industry | Description | Notebook |
|---|---|---|---|
| 🤖 Automated Task Solving with Code Gen, Execution & Debugging | Software Development | Demonstrates automated task-solving by generating, executing, and debugging code | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_auto_feedback_from_code_execution) |
| 🧑‍💻 Code Generation and Q&A with Retrieval Augmented Agents | Software Development | Generates code and answers questions using retrieval-augmented methods | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_RetrieveChat) |
| 🧠 Code Generation and Q&A with Qdrant-based Retrieval | Software Development | Utilizes Qdrant for enhanced retrieval-augmented agent performance | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_RetrieveChat_qdrant) |

**Multi-Agent Collaboration**

| Use Case | Industry | Description | Notebook |
|---|---|---|---|
| 🤝 Group Chat (3 members, 1 manager) | Collaboration | Demonstrates group task-solving via multi-agent collaboration | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_groupchat) |
| 📊 Data Visualization by Group Chat | Data Analysis | Uses multi-agent collaboration to create data visualizations | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_groupchat_vis) |
| 🧩 Complex Task Solving by Group Chat (6 members) | Collaboration | Solves complex tasks collaboratively with a larger group | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_groupchat_research) |
| 🧑‍💻 Task Solving with Coding & Planning Agents | Planning & Dev | Combines coding and planning agents for solving tasks | [](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_planning.ipynb) |
| 📐 Task Solving with Graph Transition Paths | Collaboration | Uses predefined transition paths in a graph for solving tasks | [](https://microsoft.github.io/autogen/docs/notebooks/agentchat_groupchat_finite_state_machine) |
| 🧠 SocietyOfMindAgent Inner-Monologue | Cognitive Sciences | Simulates inner-monologue for problem-solving using group chats | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_society_of_mind) |
| 🔧 Group Chat with Custom Speaker Selection | Collaboration | Implements a custom function for speaker selection | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_groupchat_customized) |

**Sequential Multi-Agent Chats**

| Use Case | Industry | Description | Notebook |
|---|---|---|---|
| 🔄 Sequential Task-Solving (single initiating agent) | Workflow Automation | Automates sequential task-solving with a single initiating agent | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_multi_task_chats) |
| ⏳ Async Sequential Task-Solving | Workflow Automation | Handles asynchronous task-solving in a sequence of chats | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_multi_task_async_chats) |
| 🤝 Sequential Chats with Different Initiating Agents | Workflow Automation | Sequential task-solving with different agents initiating each chat | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchats_sequential_chats) |

**Nested Chats**

| Use Case | Industry | Description | Notebook |
|---|---|---|---|
| 🧠 Solving Complex Tasks with Nested Chats | Problem Solving | Uses nested chats to solve hierarchical and complex problems | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_nestedchat) |
| 🔄 Sequence of Nested Chats | Problem Solving | Demonstrates sequential task-solving using nested chats | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_nested_sequential_chats) |
| 🏭 OptiGuide Supply Chain with Nested Chats | Supply Chain | Solves supply chain optimization using nested chats | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_nestedchat_optiguide) |
| ♟️ Conversational Chess with Nested Chats | Gaming | Uses nested chats for playing conversational chess with tools | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_nested_chats_chess) |

**Tools**

| Use Case | Industry | Description | Notebook |
|---|---|---|---|
| 🌐 Web Search: Solve Tasks Requiring Web Info | Information Retrieval | Searches the web to gather information for completing tasks | [](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_web_info.ipynb) |
| 🔧 Use Provided Tools as Functions | Tool Integration | Demonstrates how to use pre-provided tools as callable functions | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_function_call_currency_calculator) |
| 📚 RAG Group Chat | Collaboration | Enables group chat with Retrieval Augmented Generation | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_groupchat_RAG) |
| 🔊 Agent Chat with Whisper | Audio Processing | AI agent for transcription and translation using Whisper | [](https://microsoft.github.io/autogen/0.2/docs/notebooks/agentchat_video_transcript_translate_with_whisper) |
| 📊 SQL: Natural Language to SQL Query | Database Management | Converts natural language inputs into SQL queries | [](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_sql_spider.ipynb) |

**Multimodal Agents**

| Use Case | Industry | Description | Notebook |
|---|---|---|---|
| 🎨 Multimodal Agent with DALLE and GPT-4V | Multimedia AI | Combines DALLE and GPT-4V for multimodal agent communication | [](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_dalle_and_gpt4v.ipynb) |
| 🖌️ Multimodal Agent with Llava | Image Processing | Uses Llava for multimodal agent conversations | [](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_lmm_llava.ipynb) |
| 🖼️ Multimodal Agent with GPT-4V | Multimedia AI | Leverages GPT-4V for visual and conversational interactions | [](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_lmm_gpt-4v.ipynb) |

**Observability & Evaluation**

| Use Case | Industry | Description | Notebook |
|---|---|---|---|
| 📊 AgentEval: Multi-Agent Assessment System | Performance Evaluation | Evaluating LLM-based application utility | [](https://github.com/microsoft/autogen/blob/0.2/notebook/agenteval_cq_math.ipynb) |
| 📊 Track LLM Calls and Errors using AgentOps | Monitoring & Analytics | Monitors LLM interactions, tool usage, and errors | [](https://github.com/microsoft/autogen/blob/0.2/notebook/agentchat_agentops.ipynb) |
| 🏗️ Auto Build Multi-agent System with AgentBuilder | AI Development | Automatically builds multi-agent systems | [](https://github.com/microsoft/autogen/blob/0.2/notebook/autobuild_basic.ipynb) |

---

### Agno

Lightweight, fast agent framework. Best for single-agent tools and rapid prototyping.

| Use Case | Industry | Description | Code |
|---|---|---|---|
| 🤖 Support Agent | AI Framework Support | Real-time answers, explanations, and code examples for Agno framework | [](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/agno_support_agent.py) |
| 🎥 YouTube Agent | Media & Content | Analyzes YouTube videos: summaries, timestamps, themes | [](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/youtube_agent.py) |
| 📊 Finance Agent (Thinking) | Finance | Real-time stock insights, analyst recommendations, financial deep-dives | [](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/thinking_finance_agent.py) |
| 📚 Study Partner | Education | Finds resources, answers questions, creates study plans | [](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/study_partner.py) |
| 🛍️ Shopping Partner Agent | E-commerce | Product recommender based on preferences from Amazon, Flipkart | [](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/shopping_partner.py) |
| 🎓 Research Scholar Agent | Education / Research | Advanced academic searches, publication analysis, structured reports | [](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/research_agent_exa.py) |
| 🧠 Research Agent | Media & Journalism | Deep investigations, NYT-style reports | [](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/research_agent.py) |
| 🍳 Recipe Creator | Food & Culinary | Personalized recipes based on ingredients and preferences | [](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/recipe_creator.py) |
| 🧠 Financial Reasoning Agent | Finance | Claude 3.5 Sonnet-based stock analysis with Yahoo Finance data | [](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/reasoning_finance_agent.py) |
| 🤖 Readme Generator Agent | Software Dev | Generates high-quality READMEs for GitHub repos | [](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/readme_generator.py) |
| 🎬 Movie Recommendation Agent | Entertainment | Personalized movie recommendations using Exa and GPT-4o | [](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/movie_recommedation.py) |
| 🔍 Media Trend Analysis Agent | Media & News | Analyzes emerging trends and influencers from digital platforms | [](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/media_trend_analysis_agent.py) |
| ⚖️ Legal Document Analysis Agent | Legal Tech | Analyzes legal PDFs and provides insights using vector embeddings | [](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/legal_consultant.py) |
| 🤔 DeepKnowledge | Research | Iterative search through knowledge base with deep reasoning | [](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/deep_knowledge.py) |
| 📚 Book Recommendation Agent | Publishing & Media | Personalized book suggestions using literary data and reader preferences | [](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/book_recommendation.py) |
| 🏠 MCP Airbnb Agent | Hospitality | Search Airbnb listings with MCP and Llama 4 | [](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/airbnb_mcp.py) |
| 🤖 Agno Assist Agent | AI Framework | GPT-4o agent for Agno framework Q&A with hybrid search | [](https://github.com/agno-agi/agno/blob/main/cookbook/examples/agents/agno_assist.py) |

---

### LangGraph

State-machine framework for complex, stateful agent workflows and RAG pipelines.

| Use Case | Industry | Description | Code |
|---|---|---|---|
| 🤖 Chatbot Simulation Evaluation | AI / QA | Simulate user interactions to evaluate chatbot performance | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/chatbot-simulation-evaluation/agent-simulation-evaluation.ipynb) |
| 🧠 Information Gathering via Prompting | Research | LangGraph workflow using prompting to gather information | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/chatbots/information-gather-prompting.ipynb) |
| 🧠 Code Assistant with LangGraph | Software Development | Resilient code assistant with error checking and iterative refinement | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/code_assistant/langgraph_code_assistant.ipynb) |
| 🧑‍💼 Customer Support Agent | Customer Support | Graph-based agent for handling customer inquiries | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/customer-support/customer-support.ipynb) |
| 🔁 Extraction with Retries | Data Extraction | Retry mechanisms for robust data extraction | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/extraction/retries.ipynb) |
| 🧠 Multi-Agent Workflow (Supervisor) | Workflow Orchestration | Supervisor agent orchestrating multiple specialized agents | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/multi_agent/agent_supervisor.ipynb) |
| 🧠 Hierarchical Agent Teams | Workflow Orchestration | Top-level supervisor delegates to specialized sub-agents | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/multi_agent/hierarchical_agent_teams.ipynb) |
| 🤝 Multi-Agent Collaboration | Workflow Orchestration | Multiple specialized agents working together on complex tasks | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/multi_agent/multi-agent-collaboration.ipynb) |
| 🧠 Plan-and-Execute Agent | Workflow Orchestration | Agent generates multi-step plan then executes sequentially | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/plan-and-execute/plan-and-execute.ipynb) |
| 🧠 SQL Agent | Database Interaction | Agent answers questions about SQL databases | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/sql-agent.ipynb) |
| 🧠 Reflection Agent | Workflow Orchestration | Agent critiques and revises its own outputs | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/reflection/reflection.ipynb) |
| 🧠 Reflexion Agent | Workflow Orchestration | Agent reflects on actions for iterative improvement | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/reflexion/reflexion.ipynb) |
| 🧠 Adaptive RAG | Information Retrieval | Dynamic retrieval adjusting based on query complexity | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/rag/langgraph_adaptive_rag.ipynb) |
| 🤖 Agentic RAG | Intelligent Agents | Agent determines best retrieval strategy before generating response | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/rag/langgraph_agentic_rag.ipynb) |
| 🧠 Corrective RAG (CRAG) | Information Retrieval | Evaluates and refines retrieved documents before generation | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/rag/langgraph_crag.ipynb) |
| 🧠 Self-RAG | Information Retrieval | System reflects on responses and retrieves additional info if needed | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/rag/langgraph_self_rag.ipynb) |
| 🧠 Adaptive RAG (Local) | Information Retrieval | Adaptive RAG with local models for offline use | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/rag/langgraph_adaptive_rag_local.ipynb) |
| 🧠 Self-RAG (Local) | Information Retrieval | Self-RAG using local models and data sources | [](https://github.com/langchain-ai/langgraph/blob/main/docs/docs/tutorials/rag/langgraph_self_rag_local.ipynb) |

---

## 🤝 Contributing

Contributions are welcome! 🎉 This repo grows through community contributions.

**Ways to contribute:**
1. **Add a working agent** — create a folder in `agents/` with runnable code
2. **Add an external link** — add a row to the industry or framework tables
3. **Fix a broken link** — open an issue or PR
4. **Improve documentation** — fix typos, add context, improve examples

**To contribute:**
1. Fork the repository
2. Create a branch: `feat/agent-name` or `fix/description`
3. Add your changes following the [Contributing Guidelines](CONTRIBUTION.md)
4. Open a PR using the PR template

See [CONTRIBUTION.md](CONTRIBUTION.md) for full requirements (metadata.yaml, requirements.txt, etc.).

---

## Star History


  
  
  


---

## 📜 License

This repository is licensed under the MIT License. See the [LICENSE](LICENSE) file for more information.

---