A technical guide to the Claude Agent SDK, which enables LLMs to function as tool-using software agents. Details the core 'agentic feedback loop' (Gather, Act, Verify), and key architectural components including context management via a filesystem, the use of subagents for parallelism, and the design of effective tools (Bash, Code, MCP). Emphasizes building reliable agents through verification loops and provides best practices for production-grade systems.

A step-by-step tutorial on advancing beyond basic Claude Code usage. Covers setting up and using Claude Code within an IDE like VS Code or Cursor, creating and invoking custom 'Skills' to standardize repeatable workflows, connecting to third-party MCP servers (like Hugging Face) to grant the agent new capabilities, and extending its power with compatible open-source models like SERA.

Gemini CLI is an open-source AI agent from Google that operates directly in your terminal, featuring built-in tools for file operations, web search, code execution, and extensibility through MCP servers. Covers installation, configuration, tool usage, MCP server setup (GitHub, Cloud Run), and practical use cases from code generation to database operations and automation.

This document provides a comprehensive guide to AutoGPT, an open-source platform for building and running autonomous AI agents. It covers the core components (Frontend, Server), self-hosting requirements using Docker, and the classic toolset including Forge for agent creation and Benchmark for performance evaluation. The licensing model, which combines Polyform Shield and MIT licenses, is also explained.

A guide to the AutoGPT platform, an open-source tool for creating and deploying autonomous AI agents. Details system requirements for self-hosting, explains the roles of the AutoGPT Frontend and Server, and introduces associated projects like Forge for building custom agents and agbenchmark for performance testing.

n8n is a visual, node-based workflow automation platform that enables developers and technical users to build complex, multi-step automations. While fundamentally a deterministic automation platform, its AI Agent node enables agentic capabilities, bridging rule-based processes and dynamic AI-driven reasoning. Covers core architectural concepts (node-based canvas, trigger nodes, AI Agent node, standard nodes, data flow with expressions) for building AI-powered workflows.

OpenAI AgentKit is a comprehensive framework for designing, visualizing, and deploying multi-step AI agents. Combines drag-and-drop simplicity of low-code platforms with the power of LLM-driven decision-making and autonomy. Emphasizes visual workflow design, integration management, and safety governance, allowing for adaptive and scalable AI deployments inside the OpenAI ecosystem.

OpenAI's GPTs (custom GPTs) provide a no-code or low-code interface for creating specialized versions of ChatGPT that function as simple AI agents. Combines custom instructions (defining purpose and goal), proprietary knowledge files, and a set of predefined tools (web browsing, image generation, custom Actions). Unlike pro-code frameworks like Microsoft Agent Framework, GPTs offer an accessible entry point for building task-oriented agents directly within the ChatGPT ecosystem.