Best AI Agents Tools

Open-source, general-purpose AI agent framework that runs in a Docker sandbox and learns by writing its own tools.

Key Features:

• •Dockerized sandbox with shell, Python, browser
• •Self-improving knowledge directory of saved tools
• •Subordinate-agent dispatching

Open-source multi-agent platform from Alibaba's DAMO Academy for building LLM agents with visual workflows and runtime management.

Key Features:

• •Multi-agent framework with actor-style message passing
• •Visual Studio for drag-and-drop agent workflows
• •Built-in tools for memory, retrieval, code execution and computer use

Microsoft's full managed platform for building, deploying, and scaling enterprise AI agents with native integration into Microsoft 365, Azure services, and 1,400+ business systems through code-first SDK and visual portal experiences

Key Features:

• •No-Code Agent Builder
• •Code-Based Deployment
• •Managed Long-Term Memory

Open-source, extensible AI agent from Block that runs on your machine and orchestrates LLMs, MCP tools, and developer workflows.

Key Features:

• •Open-source AI agent (Apache 2.0) from Block
• •Desktop app and CLI
• •First-class MCP extension/tool system

Open-source Python framework for orchestrating role-playing, autonomous AI agents that collaborate as a 'crew' to complete complex tasks.

Key Features:

• •Workflow Runtime
• •Tool and API Connectivity
• •State and Context Handling

Cloud desktops for AI agents — give Claude Code, Codex or any computer-use agent its own isolated macOS or Linux VM.

Key Features:

• •Cloud macOS, Linux and Windows VMs purpose-built for agents
• •Pre-wired for Claude Code, Codex, OpenClaw and Computer Use
• •MCP-native desktop control API

Dust review 2026: enterprise AI platform from Paris for building governed agents grounded in Slack, Drive, Notion — features, pricing, pros, cons.

Key Features:

• •Visual app builder for designing multi-step LLM workflows without code
• •Managed retrieval-augmented generation (RAG) with semantic search over connected data
• •Multi-model support across GPT-4, Claude, Mistral, and other LLMs

Goose supports local agent, extensible tools, model flexibility for developer task automation and local agent workflows.

Key Features:

• •Open-source local desktop agent and CLI
• •MCP-first tool and extension architecture
• •Bring-your-own model provider credentials

Open-source self-improving AI agent framework by Nous Research with persistent memory, 40+ tools, and 135K+ GitHub stars.

Key Features:

• •Self-improving learning loop that builds skills from experience
• •Persistent memory across sessions with knowledge accumulation
• •40+ built-in tools for file management, browsing, code execution

Durable-execution platform for AI workflows and agents — write step-functions in TypeScript or Python, get retries, scheduling and observability for free.

Key Features:

• •Step-based function execution with automatic retries
• •Event-driven workflow triggering and orchestration
• •Local development server with production parity

Manus AI review covering autonomous computer workflows, artifact creation, observed features, unverified pricing, practical use cases, risks, and alternatives.

Key Features:

• •Autonomous agent with virtual computer, browser, and Python execution
• •Deliverable-oriented: produces reports, sites, decks, spreadsheets, code artefacts
• •Session replay and forking so any run can be inspected or reused

TypeScript-native framework for building AI agents, workflows, and RAG pipelines — from the team behind Gatsby.js.

Key Features:

• •TypeScript-first agentic framework for agents, tools, memory, and instructions
• •Durable workflows and typed control flow
• •Observability with metrics, logs, and traces

Enterprise platform for autonomous customer and employee agents, with explicit MCP support.

Key Features:

• •Agentforce Builder for configuring, testing, and deploying agents within Salesforce; availability and prerequisites depend on the applicable Salesforce edition and products (source: https://help.salesforce.com/s/articleView?id=ai.agentforce.htm&type=5).
• •Agent Script for defining agent behavior with instructions and reasoning controls; availability may depend on the applicable Agentforce release and account configuration (source: https://help.salesforce.com/s/articleView?id=ai.agentforce.htm&type=5).
• •Agentforce Voice for supported voice deployments; telephony provider, region, product, and channel availability must be verified for each implementation (source: https://www.salesforce.com/agentforce/voice/).

Cloud platform for building, deploying, and scheduling persistent AI workers from chat — backed by hundreds of pre-built tools and full MCP support.

Key Features:

• •AI Agent Development
• •Business Automation
• •No-Code Platform

Goose Desktop supports running assisted desktop workflows and connecting local and remote mcp tools with desktop agent interface, extensible tool connections, local workflow automation.

Key Features:

• •Desktop agent interface for multi-step development work
• •Extensions that connect local tools and MCP servers
• •Choice of model provider with local workflow execution