Showing 24 of 100 tools
Open-source personal AI agent for messaging apps
OpenClaw is a free, open-source AI agent framework that turns any LLM into an autonomous personal assistant accessible through messaging apps like WhatsApp, Telegram, Discord, and Signal. Running entirely on your local machine via a Node.js gateway, it connects AI models to system tools, browsers, files, and APIs for multi-step task execution with persistent memory across sessions.
Autonomous scientific discovery via agentic tree search
AI Scientist v2 is Sakana AI's open-source system for fully autonomous scientific research using LLM-powered agentic tree search. It generates hypotheses, designs experiments, writes and executes code, analyzes results, and produces publishable manuscripts without human intervention. The system uses progressive exploration with backtracking to navigate the research space efficiently.
Unified Python/.NET framework for multi-agent AI
Microsoft Agent Framework is Microsoft's official unified SDK for building multi-agent AI workflows in Python and .NET. It consolidates Semantic Kernel and AutoGen into a single framework with MCP tool integration, graph-based workflows, human-in-the-loop patterns, and multi-agent orchestration. The framework reached Release Candidate status in February 2026 and is Microsoft's recommended path for production agent development.
AI chatbot framework for WeChat with multi-model and plugin support
chatgpt-on-wechat is an open-source framework for deploying AI chatbots on WeChat, the dominant messaging platform in China. It supports OpenAI, Claude, Gemini, Qwen, and local models through a plugin architecture. Features group chat management, image generation, voice messages, and knowledge base integration. Over 42,700 GitHub stars reflecting massive adoption in the Chinese developer community.
Alibaba's agent framework built for the Qwen model family
Qwen-Agent is Alibaba's open-source framework for building AI agents powered by the Qwen model family. It provides tool use, planning, memory, and multi-agent orchestration with native optimization for Qwen models including function calling and code interpretation. Supports RAG, browser automation, and custom tool development with over 15,900 GitHub stars.
Framework for converting MCP servers into autonomous AI agents with UI
Nanobot transforms MCP servers into full autonomous agents by adding a planning layer, conversation memory, and web-based UI on top of MCP tool capabilities. It enables building agents that combine multiple MCP servers with LLM reasoning to complete multi-step tasks. Features MCP-UI for browser-based interaction and supports any MCP-compatible tools as agent capabilities.
AWS open-source SDK for building model-driven AI agents
Strands Agents is an open-source SDK from AWS that takes a model-driven approach to building AI agents. Developers define a prompt, model, and tools, and the LLM handles planning and orchestration autonomously. Supports Amazon Bedrock, Anthropic, OpenAI, Gemini, Ollama, and more. Powers Amazon Q Developer and AWS Glue in production. Available in Python and TypeScript with native MCP support.
Kotlin-native AI agent framework by JetBrains with MCP support
Koog is JetBrains official Kotlin-native framework for building predictable, fault-tolerant AI agents. It provides structured agent workflows with MCP protocol support, type-safe tool definitions, and deterministic execution patterns designed for JVM production environments. As the first production-grade Kotlin agent framework, it fills the gap in a JVM ecosystem dominated by Python-based alternatives and integrates naturally with existing Kotlin and Java backend infrastructure.
Production RAG engine with hybrid search and knowledge graphs
R2R is a production-grade RAG engine from SciPhi AI that combines hybrid search with knowledge graph extraction and agentic retrieval capabilities. It provides a complete pipeline from document ingestion through retrieval and generation, supporting vector, keyword, and graph-based search strategies. The managed API and self-hosted options make it accessible for both rapid prototyping and production deployments requiring advanced retrieval beyond simple vector similarity.
Kubernetes-native framework for DevOps AI agents
kagent is a Kubernetes-native AI agent framework developed at Solo.io and accepted into the CNCF sandbox. It provides a structured environment for running DevOps-focused agents directly within Kubernetes clusters, with a dedicated kmcp toolkit for cloud-native operations. Unlike general-purpose agent frameworks, kagent targets platform engineers and SREs who need AI assistance with cluster management, troubleshooting, and infrastructure automation workflows.
Open-source general AI agent framework from the MetaGPT team
OpenManus is an open-source framework for building general-purpose AI agents, developed by core contributors from the MetaGPT community. It provides a modular architecture with planning agents, reactive agents, and tool-calling agents that can execute code, browse the web, search for information, and handle files. Built as the open alternative to Manus AI, it gained over 55,000 GitHub stars and supports multi-agent collaboration with real-time execution feedback.
Rust-based agent OS with built-in security, WASM sandboxing, and multi-agent runtime
OpenFang is an open-source agent operating system built in Rust that provides a secure multi-agent runtime with WASM sandboxing, auditability layers, and multi-channel communication. It goes beyond typical orchestration SDKs by treating agent security and operational isolation as first-class concerns, making it suitable for teams deploying agents in environments where trust boundaries and audit trails matter.
Behavioral control layer for reliable customer-facing AI agents
Parlant is an open-source framework that adds behavioral governance to conversational AI agents. Instead of relying on prompt engineering alone, it lets teams define explicit policies, conversation guidelines, and behavioral rules that agents follow predictably across multi-turn interactions. Parlant sits between the LLM and the user-facing interface, enforcing consistent agent behavior for customer support, sales, and service automation use cases.
Multi-agent orchestration layer for OpenAI Codex CLI
Oh My Codex (OMX) transforms OpenAI Codex CLI into a coordinated multi-agent system. It layers workflow orchestration, persistent memory, team-based parallel execution via tmux worktrees, and a live HUD dashboard on top of standard Codex. OMX provides 30+ role-specialized agents and 40+ workflow skills covering planning, execution, verification, TDD, security review, and autonomous research loops.
Open-source framework for real-time voice and multimodal AI agents
Pipecat is an open-source framework with 11,000+ GitHub stars for building real-time voice and multimodal AI agents. Developed by Daily.co, it manages the STT to LLM to TTS pipeline with sub-second latency, integrating with AWS Bedrock, NVIDIA NIM, and AssemblyAI for production-grade voice agent deployment.
Single-file memory layer replacing complex RAG for AI agents
Memvid is an open-source single-file memory system for AI agents with 13,700+ GitHub stars. It replaces complex RAG infrastructure with instant retrieval from portable .mv2 files, claiming 35% accuracy improvement over state-of-the-art on LoCoMo benchmarks with 0.025ms P50 latency. Available for Python, Node.js, Rust, and CLI.
Transparent AI agent framework with 100+ skills and real-time visibility
Agent Zero is an open-source general-purpose AI agent framework with 16,700+ GitHub stars that uses the computer itself as a tool. Unlike structured orchestration frameworks, it provides full transparency where every thought, action, and tool call is visible and editable in real time, supporting 100+ extensible skills.
Enterprise-grade RAG and MCP knowledge base with one-click deployment
MaxKB is an enterprise-grade RAG platform with 21,000+ GitHub stars from the 1Panel team. It provides one-click deployment of knowledge bases with built-in LLM integration, MCP support, and a streamlined approach to document ingestion and retrieval that prioritizes operational simplicity over configuration complexity.
No-code knowledge base platform with visual AI workflow and built-in RAG
FastGPT is an open-source no-code AI knowledge base platform with 27,000+ GitHub stars and 500,000+ users worldwide. It combines visual workflow orchestration, built-in RAG pipelines, QA-pair extraction, and API-aligned completions into a single deployable stack that runs on just 2GB RAM via Docker one-liner deployment.
Multi-agent software company simulation for automated development
ChatDev simulates an entire virtual software company through multi-agent collaboration where LLM-powered roles including CEO, CTO, programmer, tester, and designer work together to produce complete software. With 32,000+ GitHub stars and a NeurIPS 2025 accepted paper, it offers a novel approach to automated software development through role-based agent orchestration.
Twelve-lesson curriculum for building AI coding agents from scratch
Learn Claude Code is a comprehensive educational framework with 12 structured lessons teaching AI coding agent construction from first principles. With over 46,000 GitHub stars and 7,000 forks, it provides complete runnable Python implementations progressing from a 50-line bash agent to a 550-line skills agent with modular extensibility and subagent orchestration.
Open-source sandboxes and SDKs for AI agents that control desktops
CUA is an open-source infrastructure platform for building, benchmarking, and deploying AI agents that autonomously control full desktop environments. It provides secure sandboxed VMs across macOS, Linux, Windows, and Android with a unified Python SDK for screenshots, mouse/keyboard control, shell commands, and file I/O. Includes CuaBot CLI for running agents in sandboxes, Cua-Bench for standardized evaluation, and Lume for near-native macOS virtualization on Apple Silicon.
The 5MB open-source agent daemon that hides nothing
CrabTalk is a lightweight five-megabyte daemon that streams every AI agent event to your client in real time including text deltas, tool calls, and thinking steps. It provides complete transparency into agent operations with one-curl installation and bring-your-own-model support. Designed as the observable alternative to opaque agent runtimes where you cannot see what the AI is actually doing.
Google's official Agent Development Kit for building AI agents in Go
adk-go is Google's official Agent Development Kit for the Go programming language, providing the tools and abstractions needed to build production AI agents. It supports tool calling, multi-turn conversations, structured outputs, and integration with Google's Gemini models. With 7,300 GitHub stars and Apache 2.0 license, it brings first-class AI agent development capabilities to the Go ecosystem.
