Open Source Windows OpenClaw Tools
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OpenClaw Tools for Windows
View 23 business solutionsBrowse free open source OpenClaw Tools and projects for Windows below. Use the toggles on the left to filter open source OpenClaw Tools by OS, license, language, programming language, and project status.
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OpenClaw
Your own personal AI assistant. Any OS. Any Platform.
OpenClaw (formerly Clawdbot/Moltbot) is an open-source, self-hosted autonomous AI assistant designed to run on user-controlled hardware and bridge conversational natural language with real-world task execution, effectively acting as a proactive digital assistant rather than a reactive chatbot. It lets you send instructions through familiar messaging platforms like WhatsApp, Telegram, Discord, Slack, Signal, iMessage, and more, and then interprets those instructions to carry out actions such as managing calendars, sending emails or messages, browsing the web, executing system commands, and coordinating workflows across services — all while maintaining long-term memory and context across sessions. Because it runs locally or on infrastructure you choose (like a personal computer, VPS, or Raspberry Pi), OpenClaw emphasizes data ownership, privacy, and full transparency into how your instructions are handled and what actions are taken, giving users autonomy over their AI workflows. -
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ClawX
Desktop app that provides a graphical interface for OpenClaw AI
ClawX is a cross-platform desktop application that provides a graphical user interface for OpenClaw AI agents, transforming complex command-line orchestration into an accessible visual experience. Built with Electron, React, and TypeScript, the software embeds the OpenClaw runtime directly into the application to deliver a battery-included setup without requiring separate installations. The platform focuses on usability by offering a guided setup wizard, visual configuration panels, and real-time validation, enabling users to deploy AI agents without terminal expertise. ClawX includes a modern chat interface that supports multiple conversation contexts, Markdown rendering, and persistent message history. It also supports automation through cron-based scheduling and allows users to manage multiple AI channels simultaneously for different workflows. -
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AionUi
Free, local, open-source Cowork for Gemini CLI, Claude Code, Codex
AionUi is an open-source, cross-platform graphical interface that turns command-line AI tools into a unified coworking desktop for interacting with multiple local AI agents and CLI models like Gemini CLI, Claude Code, Codex, Qwen Code, and others. Instead of forcing users to work in separate terminals for each tool, AionUi automatically detects installed CLI tools and provides a central visual workspace where sessions can run in parallel, contexts are preserved, and conversations are saved locally without sending data to external servers. It enhances productivity by offering smart file management features like batch renaming, automatic organization, and intelligent file classification, thereby reducing manual overhead when working with large datasets or complex document structures. AionUi also supports a remote WebUI mode, allowing users to access their local AI tools securely over a network from other devices while keeping all processing and data on their own hardware. -
4
OpenClaw Installer
ClawdBot one-click deployment tool
OpenClaw Installer is an open-source one-click deployment and configuration tool for installing OpenClaw — a personal AI assistant — onto systems with minimal manual setup, giving users a streamlined path to get their own AI assistant running quickly. The project provides shell scripts and configuration menus that detect the host environment, install dependencies, download OpenClaw, configure core settings like AI models and identity channels, and start the server automatically. It supports multiple platforms, including macOS, Linux distributions (Ubuntu, Debian, CentOS), and Windows environments via compatible shells, and simplifies otherwise complex installation steps into a guided, terminal-based experience. The tool also includes options to test API connections, validate channel integrations like Telegram or Discord bots, and launch persistent services that keep OpenClaw running in the background. -
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PicoClaw
Ultra-Efficient AI Assistant in Go
PicoClaw is an ultra-lightweight, open-source personal AI assistant written in Go, architected from the ground up to operate with extremely low memory usage (under 10 MB) and fast boot times, making it suitable for inexpensive hardware platforms and embedded devices. Inspired by earlier AI assistant projects like “nanobot,” it was refactored to emphasize resource efficiency while still supporting meaningful AI-driven interactions such as conversational workflows, planning tasks, and automation. PicoClaw can run on hardware costing as little as $10 and on resource-constrained environments like RISC-V or ARM boards, with cross-architecture portability achieved through a single self-contained binary. The project’s goals include broad platform support (including Linux, macOS, and multiple CPU architectures), rapid startup times that make the assistant feel responsive, and integration with popular messaging platforms via gateways or bots. -
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llmfit
157 models, 30 providers, one command to find what runs on hardware
llmfit is a terminal-based utility that helps developers determine which large language models can realistically run on their local hardware by analyzing system resources and model requirements. The tool automatically detects CPU, RAM, GPU, and VRAM specifications, then ranks available models based on performance factors such as speed, quality, and memory fit. It provides both an interactive terminal user interface and a traditional CLI mode, enabling flexible workflows for different user preferences. llmfit also supports advanced configurations including multi-GPU setups, mixture-of-experts architectures, and dynamic quantization recommendations. By presenting clear performance estimates and compatibility guidance, the project reduces the trial-and-error typically involved in local LLM experimentation. Overall, llmfit serves as a practical decision assistant for developers who want to run language models efficiently on their own machines. -
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Cherry Studio
Cherry Studio is a desktop client that supports for multiple LLMs
Cherry Studio is a cross-platform desktop client that integrates multiple large language model providers into a unified interface for creating and using AI assistants, supporting customization and multi-model conversations. Selection Assistant with smart content selection enhancement. Deep Research with advanced research capabilities. Memory System with global context awareness. Document Preprocessing with improved document handling. MCP Marketplace for Model Context Protocol ecosystem. -
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Obsidian Skills
Agent skills for Obsidian
Obsidian-Skills is a repository of agent skills tailored for use with Obsidian and any Claude-compatible agent that follows the standard Agent Skills specification, enabling AI assistants to better understand and interact with Obsidian content. These skills are markdown-driven specifications that teach Claude Code (or similar agents) how to perform context-aware tasks within Obsidian’s unique environment, such as interpreting different file types and workflows, automating workflows tied to notes, or enhancing agent responses with structured knowledge. By providing formal descriptions of patterns, conventions, and workflows common to Obsidian users, the skills empower AI tools to give more relevant suggestions, generate content that adheres to user conventions, or execute complex multi-step operations that respect the knowledge graph and file relationships. -
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OpenMontage
World's first open-source, agentic video production system
OpenMontage is an open-source, agent-driven video production system that transforms AI coding assistants into fully automated multimedia creation pipelines. Instead of focusing on a single capability such as text-to-video generation, it treats video production as a structured, multi-stage workflow that mirrors how a real production team operates, including research, scripting, asset generation, editing, and final rendering. The system orchestrates a large collection of tools and models through coordinated pipelines, enabling an AI agent to autonomously gather information, write scripts, generate visuals, synthesize voiceovers, and assemble a complete video output. One of its defining characteristics is its modular and extensible architecture, which allows users to mix and match different providers, including both cloud APIs and local models, depending on performance, cost, or privacy needs. -
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nanobot
🐈 nanobot: The Ultra-Lightweight Clawdbot / OpenClaw
nanobot is an ultra-lightweight personal AI assistant designed to deliver powerful agent capabilities without unnecessary complexity. Built in just ~4,000 lines of clean, readable code, it offers a minimalist alternative to heavyweight agent frameworks while retaining core intelligence and extensibility. nanobot is optimized for speed and efficiency, enabling fast startup times and low resource usage across environments. Its research-ready architecture makes it easy for developers to understand, customize, and extend for experimentation or production use. With simple one-click deployment and a straightforward CLI, users can get a working AI assistant running in minutes. Inspired by Clawdbot but radically simplified, nanobot proves that capable AI agents don’t need massive codebases. -
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IronClaw
IronClaw is OpenClaw inspired but focused on privacy & security
IronClaw is a security-first, open-source personal AI assistant built in Rust and designed to keep your data fully under your control. It operates on the principle that your AI should work for you, not external vendors, ensuring all data is stored locally, encrypted, and never shared. The platform emphasizes transparency, offering auditable code with no hidden telemetry or data harvesting. IronClaw runs untrusted tools inside isolated WebAssembly (WASM) sandboxes with strict capability-based permissions. It supports multiple interaction channels, including REPL, HTTP webhooks, Telegram, Slack, and a real-time web gateway. With dynamic tool building, persistent memory, and background automation, IronClaw is built to securely expand and adapt to your personal and professional workflows. -
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OpenClaw Studio
A clean web dashboard for OpenClaw
OpenClaw Studio is a web-based dashboard designed to manage and interact with OpenClaw agents through a centralized interface. It allows users to connect to an OpenClaw Gateway, monitor agents, and control workflows from a single location. The platform provides real-time chat capabilities, approval management, and job configuration tools for agent operations. Built with a control-plane architecture, it handles communication between the browser and the gateway through server-managed connections. OpenClaw Studio supports both local and cloud deployments, making it flexible for different development and production environments. It is ideal for developers and teams looking to streamline agent management and improve visibility into autonomous AI workflows. -
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OpenClaw CN
The Chinese version of OpenClaw
OpenClaw-CN is a Chinese language community adaptation and localization of the OpenClaw project, focused on making a powerful open-source agent framework usable and understandable for Chinese-speaking developers. It includes translated documentation, localized examples, and language-specific nuances so that developers in the Chinese ecosystem can adopt and contribute without a language barrier. The repository mirrors the structure of the upstream project but adds Chinese translations of core workflows, prompts, guidelines, and best practices for building multi-agent systems or AI applications. Beyond simple translation, the project often curates region-specific integrations or tooling recommendations that resonate with local developer environments and platforms. It helps accelerate adoption by providing readable guides, sample configurations, and annotated code that aligns with Chinese developer preferences and tooling conventions. -
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AutoResearchClaw
Autonomous research from idea to paper. Chat an Idea. Get a Paper 🦞
AutoResearchClaw is an open-source framework designed to automatically generate full academic research papers from a single idea or topic. Built in Python, it orchestrates a multi-stage research pipeline that gathers literature, formulates hypotheses, runs experiments, analyzes results, and writes the final paper. The system retrieves real academic references from sources such as arXiv and Semantic Scholar to ensure credible citations. It can automatically generate code for experiments, run them in a sandbox environment, and analyze the results with statistical methods. The platform also uses multi-agent debate and automated peer review processes to refine research findings and improve paper quality. By combining literature discovery, experimentation, and writing automation, AutoResearchClaw aims to turn research ideas into conference-ready papers with minimal human intervention. -
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Antigravity Claude Proxy
Proxy that exposes Antigravity provided claude / gemini models
Antigravity Claude Proxy is a purpose-built proxy server that enables developers to interface with Claude models through a standardized RESTful API, allowing tools and workflows that expect generic HTTP APIs to operate on Anthropic’s Claude without native support. The project acts as a translation layer, receiving web requests in common formats (such as OpenAI-style endpoints) and forwarding them to Anthropic’s API in the required structure, while converting responses back into a familiar shape. This makes it easier to integrate Claude into existing toolchains, scripts, notebooks, or agent frameworks that do not have built-in support for Anthropic’s native SDKs. It abstracts away key differences like authentication choreography, request schema quirks, and streaming protocols so client code can remain unchanged when switching between models. -
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OpenClaw-RL
Train any agents simply by 'talking'
OpenClaw-RL is an open-source reinforcement learning framework designed to train and personalize AI agents built on the OpenClaw ecosystem. The project focuses on enabling agents to improve their behavior through interactive learning rather than relying solely on static prompts or predefined skills. One of its key ideas is allowing users to train an AI agent simply by interacting with it conversationally, using natural language feedback to guide the learning process. The system incorporates reinforcement learning techniques to refine the agent’s policies for tool use, decision making, and task completion over time. It also explores approaches such as online policy distillation and hindsight feedback signals to strengthen training signals from real interactions. The framework operates asynchronously and does not require external API keys, making it easier to experiment with local agent training workflows. -
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NanoClaw
A lightweight alternative to Clawdbot / OpenClaw
Nanoclaw is a lightweight, security-focused personal agent runtime designed as a slimmer alternative to larger “personal assistant” agent stacks, with an emphasis on being easy to audit and safe by default. It runs agent execution inside Apple containers to provide strong isolation boundaries, so individual chats and actions can be sandboxed with tighter filesystem and process separation than a typical single-process bot. The project connects directly to WhatsApp, letting you deploy an assistant that can chat in a familiar interface while still supporting real agent behaviors instead of simple call-and-response prompts. It includes memory so the assistant can retain important context across interactions, enabling more consistent follow-through on ongoing tasks. It also supports scheduled jobs, making it suitable for recurring reminders, periodic automations, and timed workflows without needing an external orchestrator. -
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Manifest
🦞 Take control of your OpenClaw costs
Manifest is an open-source OpenClaw plugin designed to help users take control of their LLM costs through intelligent routing and real-time observability. Instead of sending every request to the same large model, Manifest intercepts each query and evaluates it using a 23-dimension scoring algorithm in under 2 milliseconds. It then routes the request to the most cost-effective and suitable model, potentially reducing costs by up to 90%. The platform includes a real-time dashboard that displays token usage, expenses, messages, and model activity in one place. Unlike cloud-based alternatives, Manifest runs entirely locally, ensuring that prompts, responses, and telemetry data never leave your machine. Built with transparency in mind, it is MIT-licensed, fully open source, and integrates natively with OpenTelemetry for standardized observability. -
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OpenClaw Chinese Translation
Open source personal AI assistant Chinese version
OpenClawChineseTranslation is a community-driven effort to provide translated resources and documentation for the OpenClaw project in Chinese, making it easier for native Chinese developers to understand and implement the agent framework. It focuses on producing accurate and up-to-date translations of tutorials, API references, configuration guides, and explanatory materials so that learners don’t struggle with language barriers when working with the original project. The repository organizes translated articles, diagrams, and examples in a way that mirrors the structure of the original codebase, helping users correlate documentation with the actual implementation. It also includes localized explanations of conceptual topics such as agent reasoning, message handling, workflow design, and best practices. -
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OpenClaw Opik Observability Plugin
Official plugin for OpenClaw that exports agent traces to Opik
OpenClaw Opik Observability Plugin is an open-source plugin designed to add observability and monitoring capabilities to OpenClaw autonomous AI agents by exporting operational traces to the Opik observability platform. The project integrates directly with OpenClaw’s plugin architecture so that developers can capture detailed runtime information about how their agents behave while executing tasks. Each time an AI agent performs an action—such as calling a large language model, invoking a tool, accessing memory, or delegating to a sub-agent—the plugin records the full interaction and sends it to Opik for analysis and visualization. This allows developers to inspect inputs, outputs, token usage, latency, and execution flow across complex multi-step agent workflows. The goal of the project is to provide transparency into the internal reasoning and operational pipeline of agent systems so developers can diagnose failures, control costs, and improve reliability. -
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openclaw-kapso-whatsapp
Give your OpenClaw AI agent a WhatsApp number
openclaw-kapso-whatsapp is a plugin repository designed to extend the OpenClaw AI agent by giving it a dedicated WhatsApp phone number using the official Meta Cloud API via Kapso, enabling direct interaction through one of the most widely used messaging platforms. This integration allows the autonomous AI assistant to send and receive messages on WhatsApp, turning the agent into a real-world task performer accessible through text conversations. The plugin is built in Go and handles communication entirely through cloud APIs, avoiding the risk of bans that come with unofficial or reverse-engineered interfaces. Projects like this make it possible for OpenClaw users to automate tasks, interact with personal contacts, or provide AI-driven services without building a custom bot infrastructure from scratch. Because OpenClaw itself runs on the user’s own hardware and can access external services, this WhatsApp extension serves as a bridge between the AI agent and daily messaging workflows. -
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Build Your Own OpenClaw
A step-by-step guide to build your own AI agent
Build Your Own OpenClaw is a step-by-step educational framework that teaches developers how to construct a fully functional AI agent system from scratch, gradually evolving from a simple chat loop into a multi-agent, production-ready architecture. The project is structured into 18 progressive stages, each introducing a new concept such as tool usage, memory persistence, event-driven design, and multi-agent coordination, with each step including both explanatory documentation and runnable code. It begins with foundational concepts like conversational loops and tool integration, then expands into more advanced capabilities such as dynamic skill loading, web interaction, and context management. As the tutorial progresses, it introduces architectural improvements including event-driven systems, WebSocket communication, and configuration hot-reloading to support scalability and real-time interaction. -
23
NemoClaw
NVIDIA plugin for secure installation of OpenClaw
NVIDIA NemoClaw is an open-source tool designed to simplify the deployment and management of always-on AI assistants using the OpenClaw ecosystem. It installs and configures the NVIDIA OpenShell runtime, which provides a secure environment for running autonomous AI agents. NemoClaw enables users to launch sandboxed agent environments that control network access, file permissions, and inference requests through policy-based security. The platform integrates with AI models such as NVIDIA Nemotron and supports multiple inference backends including cloud APIs, local NIM deployments, and vLLM. Through its command-line interface, developers can deploy, monitor, and manage AI assistants running inside isolated sandboxes. By combining sandbox orchestration, agent management, and AI model integration, NemoClaw provides a secure foundation for building and operating autonomous AI assistants. -
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OpenClaw Office
OpenClaw Office is the visual monitoring and management frontend
OpenClaw Office is a visual monitoring and management interface designed for the OpenClaw multi-agent system, providing an immersive and interactive way to observe and control autonomous AI agents. It presents agent activity through a virtual office environment, where each agent is represented as an animated entity within a 2D or 3D workspace. The platform enables real-time visualization of agent states, interactions, and workflows, making complex multi-agent coordination easier to understand and debug. Users can observe communication flows between agents through visual connections, track token usage and operational costs, and analyze performance through integrated dashboards and charts. The system also includes live chat capabilities, allowing users to monitor conversations and tool calls as they occur. -
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SafeClaw
Chat with it via text and voice
SafeClaw is an open-source, entirely local alternative to cloud-based AI assistants like OpenClaw, enabling users to build a personal assistant that runs on their own machine without incurring API usage charges or exposing data to third-party services. It emphasizes privacy and predictability by using traditional programming, rule-based intent parsing, and established machine learning tools rather than large language models, meaning there are no per-token API costs and deterministic behavior. The assistant offers features such as voice control using fully local speech-to-text (Whisper) and text-to-speech (Piper) capabilities, news aggregation with extractive summarization, and smart home or Bluetooth device control. SafeClaw supports multiple channels, including CLI and Telegram, and avoids prompt injection risk because it doesn’t rely on LLMs for core operations.
