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#jupyter_notebook #agentic_ai #agentic_framework #agentic_rag #ai_agents #ai_agents_framework #autogen #generative_ai #semantic_kernel

This course helps you learn about AI Agents from the basics to advanced levels. AI Agents are systems that use large language models to perform tasks by accessing tools and knowledge. The course includes 10 lessons covering topics like agent fundamentals, frameworks, and use cases. It provides code examples and supports multiple languages. By completing this course, you can build your own AI Agents and apply them in various applications, such as customer support or event planning, making complex tasks easier and more efficient.

https://github.com/microsoft/ai-agents-for-beginners
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#typescript #ai #ai_agents #llm

Suna is a free, open-source AI assistant that helps you do many tasks easily by talking naturally. It can browse the web, gather and analyze data, manage files, run system commands, deploy websites, and connect with many online services and APIs. You can use it for things like market research, finding leads, writing reports, planning trips, or scraping data from websites. It runs securely in isolated environments and saves your work and history. You can host it yourself for full control and privacy, making it a powerful tool to automate complex workflows and save time on everyday or professional tasks[1][2][4][5].

https://github.com/kortix-ai/suna
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#python #agent_computer_interface #ai_agents #computer_automation #computer_use #grounding #gui_agents #in_context_reinforcement_learning #memory #mllm #planning #retrieval_augmented_generation

Agent S2 is a smart AI assistant that handles computer tasks by breaking them into smaller steps and using specialized tools for each part, making it highly adaptable and efficient across different systems like Windows and Android. It outperforms other AI tools in completing complex tasks, learns from experience, and adjusts plans as needed, helping users automate digital work more reliably and effectively.

https://github.com/simular-ai/Agent-S
#python #agents #ai #ai_agents #api #developer_tools #function_calling #integration #llm #mcp #oauth2 #open_source #permissions #tools

ACI.dev is an open-source platform that helps build AI agents by providing easy access to over 600 tools. It simplifies authentication and tool integration, allowing AI agents to work with many services like Google Calendar and Slack without needing separate setups. This platform offers multi-tenant authentication, flexible access methods, and natural language permissions, making it easier to manage and secure AI agent capabilities. It's open-source and works with any framework, which means you can build AI agents without worrying about vendor lock-in.

https://github.com/aipotheosis-labs/aci
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#python #ai #ai_agents #ai_memory #cognitive_architecture #cognitive_memory #contributions_welcome #good_first_issue #good_first_pr #graph_database #graph_rag #graphrag #help_wanted #knowledge #knowledge_graph #neo4j #open_source #openai #rag #vector_database

Cognee is an open-source AI memory engine that helps improve how AI systems understand and process data. It mimics human cognitive processes, creating "memories" from various data types like text and images. This enhances the accuracy of large language models (LLMs) and allows them to recall past interactions and documents. Cognee is scalable, cost-effective, and integrates easily with existing systems, making it a valuable tool for developers seeking to boost AI performance without relying on expensive APIs.

https://github.com/topoteretes/cognee
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#python #agents #ai #ai_agents #llm #llms #mcp #model_context_protocol #python

The Model Context Protocol (MCP) is a standard way for AI agents to connect with different tools and data sources, making it much easier to build powerful AI applications without writing custom code for each integration[2][5]. The mcp-agent framework uses MCP to let you quickly create agents that can do things like read files, fetch web pages, or manage emails, and you can combine these agents in flexible ways to handle complex tasks. This means you can focus on what you want your AI to do, while mcp-agent takes care of connecting to the right tools and managing the workflow, saving you time and effort[3][5].

https://github.com/lastmile-ai/mcp-agent
#other #ai_agents #genai

You can explore a large collection of AI agent projects and use cases across many industries like healthcare, finance, education, customer service, and more. These AI agents automate tasks such as medical diagnosis, stock trading, personalized tutoring, customer support, product recommendations, and supply chain optimization. The projects include open-source code and frameworks like CrewAI, Autogen, Agno, and Langgraph, which help build, manage, and collaborate AI agents for tasks like coding, multi-agent teamwork, data analysis, and workflow automation. Using these resources can save you time, improve efficiency, and inspire you to create AI solutions tailored to your needs.

https://github.com/ashishpatel26/500-AI-Agents-Projects
#python #agent #agentic #agentic_ai #agents #agents_sdk #ai #ai_agents #aiagentframework #genai #genai_chatbot #llm #llms #multi_agent #multi_agent_systems #multi_agents #multi_agents_collaboration

The Agent Development Kit (ADK) is an open-source Python toolkit that helps you easily build, test, and deploy smart AI agents, from simple helpers to complex multi-agent systems. It lets you write agent logic in Python, use many built-in or custom tools, and organize multiple agents to work together. You can deploy agents anywhere, including Google Cloud, and evaluate their performance with built-in tools. ADK supports flexible workflows and works with various AI models, not just Google’s. This means you get full control and flexibility to create powerful AI applications that fit your needs, speeding up development and making it easier to manage AI projects.

https://github.com/google/adk-python
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#typescript #agent #agentic_ai #agents #ai #ai_agents #ai_tools #anthropic #automation #bytebot #computer_use #computer_use_agent #cua #desktop #desktop_automation #docker #gemini #llm #mcp #openai

Bytebot is an open-source AI desktop agent that acts like a virtual employee with its own computer, able to use real applications, browse websites, handle passwords, and process documents automatically. You just describe tasks in plain English, and Bytebot completes them by clicking, typing, downloading files, organizing data, and running complex workflows across multiple programs. It runs locally on your own infrastructure, ensuring privacy and full control, and supports many AI models. This helps you save time by automating repetitive or complex tasks without scripting, improving efficiency and accuracy in business, research, or development work.

https://github.com/bytebot-ai/bytebot
#typescript #agent #ai #ai_agents #ai_tools #automation #browser #browser_automation #browser_use #chrome_extension #comet #dia #extension #manus #mariner #multi_agent #n8n #nano #opensource #playwright #web_automation

Nanobrowser is a free, open-source Chrome extension that uses multiple AI agents to automate complex web tasks directly in your browser, keeping your data private since everything runs locally. It supports many AI language models, lets you customize which models handle different tasks, and offers an easy chat interface to control and track automation. You can automate repetitive tasks, ask follow-up questions, and review past interactions without coding. It works best on Chrome and Edge and is a cost-effective alternative to expensive AI automation tools, giving you powerful, flexible web automation with full control and privacy.

https://github.com/nanobrowser/nanobrowser
#python #agents #ai #ai_agents #api #developer_tools #discord #function_calling #integration #llm #mcp #mcp_client #mcp_server #oauth2 #open_source

Klavis AI helps developers connect AI tools to other services like GitHub, Gmail, and Slack easily. It offers hosted servers that handle authentication and client code automatically, making it simpler to integrate AI with various platforms. This saves time and effort by eliminating the need for custom authentication management and client library maintenance. Users can quickly set up and scale their AI applications without worrying about complex integrations, making it easier to deploy AI-powered workflows securely and efficiently.

https://github.com/Klavis-AI/klavis
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#python #agents #ai_agents #anthropic #anthropic_claude #automation #claude #claude_code #claude_code_cli #claude_code_commands #claude_code_plugin #claude_code_plugins #claude_code_subagents #claude_skills #claudecode #claudecode_config #claudecode_subagents #orchestration #sub_agents #subagents #workflows

Claude Code Plugins provide a comprehensive system of 63 focused plugins containing 85 specialized agents, 47 skills, and 44 development tools organized for intelligent automation across software development. You install only what you need, keeping token usage minimal while accessing domain experts in architecture, languages, infrastructure, quality, and operations. Each plugin loads independently with its own agents and commands, letting you compose multiple plugins for complex workflows. This granular design means faster, cleaner sessions with progressive disclosure—knowledge loads only when activated. The benefit is significant productivity gains: you get expert-level assistance tailored to your specific task without unnecessary overhead, enabling your entire team to work more efficiently on development, infrastructure, security, and automation challenges.

https://github.com/wshobson/agents
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#typescript #agent #agentic #agentic_ai #agents #agents_sdk #ai #ai_agents #aiagentframework #genai #genai_chatbot #llm #llms #multi_agent #multi_agent_systems #multi_agents #multi_agents_collaboration

Agent Development Kit (ADK) for TypeScript is an open-source toolkit to build, test, and deploy advanced AI agents with full control in code. Key features include rich tools like Google Search, custom functions, and multi-agent hierarchies for scalable apps, plus a dev UI for easy debugging. Install via npm install @google/adk. You benefit by creating flexible, versioned AI agents that integrate tightly with Google Cloud, run anywhere from laptop to cloud, and speed up development like regular software.

https://github.com/google/adk-js
#rust #agent #ai_agents #kanban #management #task_manager

Vibe Kanban is a local web tool that helps you run, manage, and review multiple AI coding agents (Claude Code, Gemini CLI, Amp, etc.) from a single Kanban-style interface, letting agents run in isolated git worktrees, parallel or sequentially, and showing live progress, diffs, and options to start dev servers or create PRs so you keep your main codebase safe and organized. Benefit: you save time and reduce errors by orchestrating agents, reviewing their changes visually, and merging only vetted work instead of juggling terminals and branches manually.

https://github.com/BloopAI/vibe-kanban
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#python #ai #ai_agents #ai_coding #claude_code_plugin #claude_code_plugins #claude_code_plugins_marketplace #claude_marketplace #claude_plugin #claude_skills #docs #documentation #mcp #mcp_server #postgres #postgresql #skills

pg-aiguide helps AI coding tools create better PostgreSQL code with semantic search of official docs, best-practice skills for schemas/indexes, and extension info like TimescaleDB. Install it free as a public MCP server or Claude plugin in tools like Cursor/VS Code for one-click setup. It fixes AI's weak spots—outdated code, missing constraints (4x more), indexes (55% more), and modern PG17 features—producing robust, fast, maintainable schemas that save you debugging time and production fixes.

https://github.com/timescale/pg-aiguide
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#python #agent #agentic_ai #agentic_framework #agentic_workflow #ai #ai_agents #ai_companion #ai_roleplay #benchmark #framework #llm #mcp #memory #open_source #python #sandbox

MemU lets AI systems take in conversations, documents, and media, turn them into structured memories, and store them in a clear three-layer file system. It offers both fast embedding search and deeper LLM-based retrieval, works with many data types, and supports cloud or self-hosted setups with simple APIs. This helps you build AI agents that truly remember past interactions, retrieve the right context when needed, and improve over time, making your applications more accurate, personal, and efficient.

https://github.com/NevaMind-AI/memU
#shell #ai #ai_agent #ai_agents #ai_development #ai_development_tools #claude_code #claude_code_cli #development_tools #development_workflow

Ralph lets Claude Code work on a software project in a loop until the tasks are truly finished, while safely avoiding infinite runs and API overuse. It can import your existing requirement documents, turn them into a structured project with tasks, and then automatically code, test, and track progress with logs and live monitoring. Built‑in session management, rate limiting, circuit breakers, and JSON‑based error handling keep long runs stable. This helps you offload repetitive development work and move faster from ideas and specs to working code.

https://github.com/frankbria/ralph-claude-code
#javascript #agent #agentic #agentic_ai #ai #ai_agents #automation #cursor #design #figma #generative_ai #llm #llms #mcp #model_context_protocol

Cursor Talk to Figma MCP lets Cursor AI read and edit your Figma designs directly, using tools like `get_selection` for info, `set_text_content` for bulk text changes, `create_rectangle` for shapes, and `set_instance_overrides` for components. Setup is quick: install Bun, run `bun setup` and `bun socket`, add the Figma plugin. This saves you hours by skipping context switches, automating repetitive tasks like text replacement or override propagation, speeding up design-to-code workflows, and keeping everything in sync for faster, precise builds.

https://github.com/grab/cursor-talk-to-figma-mcp
#html #ai_agent_tools #ai_agents #ai_tools #code_execution #code_executor #code_runner #competitive_programming #online_compiler #online_judge #online_judges #onlinejudge #onlinejudge_solution

Judge0 is a free, open-source tool that safely runs code from over 90 languages online. It's fast, scalable, and sandboxed for AI agents, coding platforms, e-learning, and job tests. Use its simple API or Python SDK to execute code easily—self-host it or try the cloud. This helps you build apps quickly without managing servers, saving time and ensuring secure code testing.

https://github.com/judge0/judge0
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