Best 60 AI Agents Tools of 2025

Swarm is an experimental framework managed by the OpenAI Solutions team, designed to build, orchestrate, and deploy multi-agent systems. It facilitates coordination and execution among agents (Agents) through the definition of abstract concepts of agents and handoffs. The Swarm framework emphasizes lightweight design, high controllability, and ease of testing, making it ideal for scenarios that require numerous independent functionalities and instructions. It allows developers complete transparency and fine-grained control over context, steps, and tool calls. The Swarm framework is currently in an experimental stage and is not recommended for production environments.

LiveKit Agents is an end-to-end framework that enables developers to construct intelligent multimodal voice assistants (AI agents) that interact with users via voice, video, and data channels. It provides a quick-start guide for creating voice assistants by integrating OpenAI's real-time API and LiveKit's WebRTC infrastructure, including pipelines for speech-to-text (STT), language models (LLM), and text-to-speech (TTS). Additionally, it supports building voice-to-voice agents, handling incoming calls, and making calls on behalf of users.

The Genspark Autopilot Agent is an intelligent agent capable of autonomously processing tasks by simulating user operations, allowing it to continue functioning even after the user closes the page. Its core advantage lies in its automation capabilities, which can significantly boost efficiency and minimize repetitive labor, enabling users to focus on more creative and strategic tasks. Developed to meet the demands for automation and efficiency in modern work environments, the Genspark Autopilot Agent is likely to offer different tiers of service to accommodate various user needs.

Windows Agent Arena (WAA) is an open-source framework dedicated to the Windows operating system for testing and developing AI agents capable of reasoning, planning, and acting using language models on PCs. It simulates a real Windows environment, allowing agents to operate freely and use the same applications, tools, and web browsers as human users to solve tasks. WAA leverages Azure for scalability and parallelization, completing comprehensive benchmark evaluations in as little as 20 minutes.

muAgent is an innovative agent framework powered by a knowledge graph engine, supporting multi-agent orchestration and collaboration technology. It leverages LLM + EKG (Eventic Knowledge Graph for industry knowledge) technology, integrating FunctionCall, CodeInterpreter, and more, to automate complex SOP processes through drag-and-drop canvas design and lightweight text scripting. muAgent is compatible with various existing agent frameworks and features core functionalities such as complex reasoning, online collaboration, human interaction, and knowledge accessibility. This framework has been validated in multiple complex DevOps scenarios at Ant Group.

Claude for Enterprise is an AI assistant product tailored for enterprise-level users, aimed at helping organizations securely leverage internal knowledge for collaboration. It provides an extended context window of 500K tokens, increased usage capacity, and native GitHub integration, enabling teams to work with Claude on full code repositories. Additionally, it includes enterprise-grade security features such as Single Sign-On (SSO), role-based permissions, and admin tools to help protect your data and team. Claude for Enterprise enhances work efficiency and quality by integrating enterprise knowledge, allowing expertise to be leveraged across more projects, decisions, and teams.

Gemini is an AI service launched by Google that allows users to create personalized AI experts through the Gems feature for specialized assistance. This service is available for Gemini Advanced, Business, and Enterprise users, supports cross-platform use, and reaches customers in over 150 countries.

Open-LLM-VTuber is an open-source project designed for interaction with large language models (LLMs) via voice, featuring real-time Live2D facial capture and cross-platform long-term memory capabilities. This project supports macOS, Windows, and Linux platforms, allowing users to select different speech recognition and speech synthesis backends, as well as customized long-term memory solutions. It is particularly suited for developers and enthusiasts looking to implement natural language conversations with AI across various platforms.

Agent Q is the next-generation AI agent model developed by MultiOn. By integrating search, self-criticism, and reinforcement learning, it creates advanced autonomous web agents capable of planning and self-repair. It addresses the challenges of traditional large language models (LLMs) in multi-step reasoning tasks within dynamic environments, enhancing success rates in complex scenarios using guided Monte Carlo Tree Search (MCTS), AI self-criticism, and Direct Preference Optimization (DPO) algorithms.

The multi-agent concierge is a system that employs multiple specialized agents to accomplish complex tasks, guided by a 'concierge' agent that directs users to the appropriate agents. This system is designed to manage multiple interdependent tasks using hundreds of tools. It demonstrates how to create implicit 'chains' between agents through natural language commands and manage these chains with 'continuation' agents, while employing a global state to track users and their current status.

The agent-service-toolkit is a comprehensive toolkit for running AI agent services based on LangGraph, including LangGraph agents, FastAPI services, clients, and Streamlit applications, providing a complete setup from agent definition to user interface. It leverages the high control capabilities and rich ecosystem of the LangGraph framework, supporting advanced features such as concurrent execution, graph loops, and streaming results.

AgentK is a self-evolving modular self-agent general artificial intelligence (AGI) model composed of multiple collaborating agents that can construct new agents based on user needs to accomplish tasks. Built on the LangGraph and LangChain frameworks, it possesses self-testing and self-repair capabilities, designed to be a minimal set of agents and tools for self-guidance and evolution of intelligence.

This is an open-source project designed for remote control of the humanoid robot Unitree H1_2. Utilizing Apple Vision Pro technology, it enables users to control robots through a virtual reality environment. The project has been tested on Ubuntu 20.04 and Ubuntu 22.04 and provides detailed installation and configuration guidance. The main advantages of this technology include offering an immersive remote control experience and supporting testing in a simulated environment, providing new solutions for the robotics remote control field.

Agent Zero is a highly transparent, readable, understandable, customizable, and interactive personal AI framework. It is not pre-programmed for specific tasks, but rather designed as a general-purpose assistant capable of executing commands and code, collaborating with other agent instances and completing tasks to the best of its abilities. It features persistent memory, enabling it to recall previous solutions, code, facts, instructions, etc., to solve future tasks more quickly and reliably. Agent Zero uses the operating system as a tool for task completion, without being limited to pre-programmed single-purpose tools. Instead, it can write its own code and create and utilize its own tools as needed through the terminal.

aiwaves-cn/agents is an open-source framework focused on data-driven adaptive language agents. It provides a systematic approach to training language agents through symbolic learning, inspired by the connectionist learning process used for training neural networks. The framework implements backpropagation and gradient-based weight updates, utilizing language-based losses, gradients, and weights to optimize multi-agent systems.

The Llama-agentic-system is a system-level agent component based on the Llama 3.1 model, capable of performing multi-step reasoning and utilizing built-in tools, such as search engines and code interpreters. This system also emphasizes security assessments with input and output filtering via Llama Guard to ensure safety requirements are met across different use cases.

Composio is a platform that provides high-quality tools and integrations for AI agents, simplifying issues of authentication, accuracy, and reliability, allowing developers to integrate various tools and frameworks with just a single line of code. It supports over 100 tools and covers more than 90 platforms, including GitHub, Notion, and Linear. Composio offers diverse functionalities, including software operations, operating system interactions, browser features, search capabilities, software development environments (SWE), and real-time agent data (RAG). Additionally, it supports six different authentication protocols, significantly increasing the accuracy with which agents can call tools. Composio can also be embedded as a backend service in applications to manage authentication and integration for all users and agents, ensuring a consistent user experience.

The IoAI (Internet of Agents) is a smart agent interconnect framework that aims to enable automation collaboration between different intelligent agents through a highly modular design. It allows developers to integrate third-party intelligent agents quickly and assign and execute tasks through a unified interface. The core advantage of IoA lies in its flexibility and scalability, supporting a wide range of application scenarios, including but not limited to collaborative paper writing, benchmarking, and open-instruction datasets.

The MacOS Agent is a simple and lightweight solution based on a large language model (LLM) using the AI application development platform - Dify. This AI assistant makes it easy for users, including children, to control MacOS with natural language commands, just like talking to a technical expert. It's not only similar to Siri, but also supports multi-round conversations, allowing users to maintain context and continuity in tasks. For example, you can ask the assistant to provide some text and then request it to convert the text into an Excel or Word file.

AutoGPT is a powerful tool that allows users to create and run smart agents that can automatically perform various tasks, making life easier. The goal of AutoGPT is to provide tools that allow users to focus on what's important. It pushes the frontier of AI innovation by building and using AI agents.

Rodel Agent is a Windows desktop application that integrates chat, text-to-image, text-to-speech, and machine translation. It supports mainstream AI services, providing an exceptional desktop AI experience for users. The product's main advantages include powerful integration features, a user-friendly interface, and support for mainstream AI services, which can significantly improve user efficiency and creativity.

OmAgent is a sophisticated multimodal intelligent agent system dedicated to leveraging multimodal large language models and other multimodal algorithms to accomplish compelling tasks. It encompasses a lightweight intelligent agent framework, omagent_core, meticulously designed to address multimodal challenges. OmAgent comprises three core components: Video2RAG, DnCLoop, and Rewinder Tool, respectively responsible for long video understanding, complex problem decomposition, and information retrieval.

xLAM is an intelligent agent research project based on Large Language Models (LLMs) developed by the Salesforce AI Research team. It aggregates intelligent agent trajectories from various environments, standardizing and unifying them into a consistent format to create an optimized general data loader specifically designed for intelligent agent training. xLAM-v0.1-r is the 0.1 version of this model series, designed for research purposes and compatible with VLLM and FastChat platforms.

Claude's Projects feature allows users to create dedicated project robot assistants. Upload project materials as a knowledge base and customize content output to boost work efficiency.

llama-agents is an asynchronous-first framework for building, iterating, and productionizing multi-agent systems. It encompasses functionalities like multi-agent communication, distributed tool execution, and human-in-the-loop (HITL) capabilities. Each agent is treated as a service, continually processing incoming tasks. Agents retrieve and publish messages from message queues. A control plane sits atop the system, tracking ongoing tasks, network services, and determining the next steps for task processing.

Agent-E is a system based on the AutoGen agent framework, designed to automate user computer operations, currently focusing on automation within the browser. It interacts with web browsers using natural language, executing tasks such as filling forms, searching and ranking products on e-commerce sites, locating website content, managing playback settings, performing web searches, and managing project management platform tasks. Agent-E is still growing and can handle diverse tasks, but the best tasks are those discovered by the user themselves.

OpenAgents is an open platform designed to enable users and developers to utilize and host language agents in their daily lives. The platform currently features three agents: a Data Agent for data analysis, processing, modification, and visualization; a Plugins Agent that integrates with 200+ everyday tools; and a Web Agent for automatic web browsing. OpenAgents empowers ordinary users to interact with agent functionalities through its optimized Web UI, while simultaneously providing developers and researchers with seamless local deployment experiences, laying the groundwork for innovative language agent construction and real-world evaluation.

Nerve is an LLM tool that enables the creation of stateful agents. Users can define and execute complex tasks without writing code. Through dynamically updated system prompts and state preservation across multiple inference steps, agents can plan and execute tasks progressively. Nerve supports any model accessible through ollama, groq, or the OpenAI API, offering high flexibility and efficiency while prioritizing memory safety.

Agent Mode is a feature of Warp AI that empowers users to accomplish multi-step workflows within the terminal using natural language. It can recognize and interpret natural language instructions, provide context-specific guidance, and lead users through complex tasks. Agent Mode leverages OpenAI's API but does not store or retain user input or output data.

agentUniverse is a multi-agent application development framework built upon large language models, providing all the essential components for constructing both single-agent and multi-agent collaborative mechanisms. Through a pattern factory, developers can construct and customize multi-agent collaboration patterns, simplifying the development of multi-agent applications and facilitating the sharing of pattern practices across different technical and business domains.