Open Source Rust AI Agents
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Rust AI Agents
View 964 business solutionsBrowse free open source Rust AI Agents and projects below. Use the toggles on the left to filter open source Rust AI Agents by OS, license, language, programming language, and project status.
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OpenAI Codex CLI
Lightweight coding agent that runs in your terminal
OpenAI Codex CLI is a lightweight, open-source coding assistant that runs directly in your terminal, designed to bring ChatGPT-level reasoning to your code workflows. It allows developers to interactively query, edit, and generate code within their repositories, all while maintaining version control. The CLI can scaffold new files, run code in sandboxed environments, install dependencies, and commit changes automatically, streamlining chat-driven development. It supports various approval modes—from suggestion-only to full automation—ensuring safe and controlled code execution. Codex CLI can also handle multimodal inputs like screenshots and diagrams to implement features intelligently. The tool includes built-in sandboxing & security measures, such as network restrictions and directory confinement, to protect your system during code execution. With extensive configuration options, including multiple AI providers and custom guidance files, it fits seamlessly into developer environments. -
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GaiaNet
Install and run your own AI agent service
Gaia is building an active, intelligent ecosystem that supports applications that learn, improve and grow over time. Put your knowledge to work and watch it evolve by creating a node on Gaia or by contributing to a domain supporting an existing knowledge base. Gaia’s decentralized platform ensures robust protection for user data and IP. Gaia allows secure ownership and monetization of IP without compromising privacy. Gaia’s living knowledge organisms continuously adapt and grow in real-time, keeping solutions relevant and cutting-edge. Developers can build applications that evolve and improve over time. -
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Obscura
The headless browser for AI agents and web scraping
Obscura is a security-focused project aimed at providing tools and techniques for enhancing privacy, anonymity, and operational security in digital environments. It is designed for users who need to obscure their digital footprint and reduce traceability across systems. The project typically includes utilities for masking identity, managing secure communication, and mitigating surveillance risks. It emphasizes practical implementations of privacy-preserving workflows rather than purely theoretical approaches. Obscura is particularly relevant for researchers, security professionals, and privacy-conscious users. Its architecture focuses on modular tools that can be adapted to different threat models. The project reflects modern concerns around digital surveillance and data exposure. -
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OpenHuman
Your Personal AI super intelligence. Private, simple and powerful
OpenHuman is an open-source personal AI assistant built to operate as a daily-life agent rather than a simple chatbot. It focuses on a private, desktop-first experience with a friendly interface, onboarding flows, and a persistent assistant that can remember context over time. The project connects to common productivity tools, gathers fresh information from integrations, and organizes user knowledge into a local memory system. It also includes practical agent tools such as web search, web fetching, file access, coding utilities, voice input, text-to-speech, and model routing. Its goal is to make an AI assistant feel continuously useful across meetings, messages, documents, tasks, and personal workflows. Since it is still in early beta, it is best suited for technical users and early adopters who want to experiment with a customizable personal AI environment. -
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Goose
AI coding agent that's more than suggestions - install, execute, edit+
Goose is an open-source, extensible AI agent that enhances the software development process by going beyond traditional code suggestions. It allows developers to install, execute, edit, and test code with any large language model (LLM), facilitating a more efficient and streamlined workflow. Designed to operate locally within a developer's environment, Goose integrates seamlessly with various tools and platforms, providing a customizable and powerful assistant for coding tasks. Its architecture supports extensibility, enabling users to tailor the agent to their specific needs and preferences. By leveraging Goose, developers can improve productivity and code quality through advanced AI-driven assistance. -
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herdr
Agent multiplexer that lives in your terminal
herdr is a terminal-native multiplexer built specifically for running AI coding agents. It gives every agent a real terminal pane instead of a simulated terminal inside a desktop wrapper. Users can organize agent sessions into workspaces, tabs, and split panes while keeping visibility into what each agent is doing. The sidebar shows whether agents are blocked, working, done, or idle, so large multi-agent workflows are easier to supervise. Sessions continue running after detach, which allows users to reconnect later from another terminal or over SSH. The project is distributed as a lightweight Rust binary for Linux, macOS, and beta Windows support. It also includes a local socket API and CLI so agents can create panes, read output, and orchestrate terminal workflows themselves. -
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AIChat
All-in-one LLM CLI tool featuring Shell Assistant
AIChat is a lightweight terminal-based chatbot powered by GPT models, enabling AI-driven conversations directly from the command line. -
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Codex-X
Codex Switch & Instruct desktop manager
Codex-X is a cross-platform desktop manager for OpenAI Codex Desktop and Codex CLI configurations. It replaces repeated manual file editing with a visual interface for prompts, providers, sessions, skills, MCP servers, and TOML settings. Users can categorize, import, edit, enable, disable, cache, and synchronize Markdown instruction templates. Provider tools store multiple API configurations, test connections, retrieve models, and switch between official and third-party services. Session management can search, group, inspect, synchronize, and permanently delete local Codex histories. The application also displays authentication and configuration files while creating backups before important changes. Packages are offered for macOS, Windows, and Linux through a Tauri-based desktop application. -
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Kheish
Kheish: A multi-role LLM agent for tasks like code auditing
Kheish is a framework designed for cybersecurity professionals to automate penetration testing tasks, providing tools to streamline security assessments. -
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aaif-goose
An open source, extensible AI agent that goes beyond code suggestions
goose is an open-source AI agent that runs locally on a user’s machine. It is built for more than coding, supporting research, writing, automation, data analysis, workflows, and general task execution. The project provides a desktop app, command-line interface, and API, which gives users multiple ways to work with the agent. goose is designed to connect with tools and local context so it can help complete practical tasks instead of only answering chat prompts. It is useful for developers, analysts, writers, and technical users who want an extensible assistant that can operate inside their environment. Its main value is bringing a native, flexible, and open agent workflow to everyday computer-based work. -
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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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ZeroClaw
Fast, small, and fully autonomous AI assistant infrastructure
ZeroClaw is a Rust-native autonomous AI agent framework engineered for teams and developers who need highly efficient, secure, and modular AI automation infrastructure that can run reliably in both production and self-hosted environments. It is designed around a trait-based architecture so that model providers, communication channels, memory systems, and tooling integrations can be swapped or extended without rewriting core components, giving engineers flexibility and long-term maintainability. The framework features a compact single binary with fast cold and warm startup times and very low memory overhead, making it suitable even for resource-constrained hardware like small servers or edge devices. Security is a first-class concern, with sandbox controls, encrypted secrets, allowlisted operations, and scoped filesystem access by default, helping reduce risk when running autonomous agents. -
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Shinkai: Local AI Agents
Shinkai allows you to create advanced AI (local) agents effortlessly
Shinkai is a free, open-source AI platform that lets anyone create powerful AI agents without coding. These agents can collaborate with each other, handle complex tasks, and operate in decentralized crypto environments. Key Features: - No-Code Agent Creation - Build specialized agents (trading bots, sentiment trackers, etc.) with simple descriptions - Multi-Agent Collaboration - Agents work together to solve complex problems - Crypto Integration - Built-in support for decentralized payments and transactions - Flexible AI Models - Choose from cloud models (GPT-4, Claude) or run locally - Universal Compatibility - Works with Model Context Protocol (MCP) for cross-platform integration - Local Security - Crypto keys and computations stay on your device Shinkai transforms AI from single-task tools into collaborative, autonomous systems that can operate in decentralized networks while maintaining privacy and security. -
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AOS Community Edition
AOS Community Edition: the open agent operating system
AOS Community Edition is an open agent operating system for building inspectable and composable agent environments. It provides the aos command-line interface, an HTTP API, community distributions, first-party capsules, provider and model controls, and Unicity Audit. The supported installer provisions a pinned runtime and a versioned collection of 21 Community Edition capsules. Local assets allow both standard and offline initialization, while coordinated upgrades preserve product compatibility. Signed release metadata, checksums, provenance attestations, and runtime compatibility files strengthen supply-chain verification. Its MCP service gives Codex, Claude, and Grok a shared product edge with constrained approval handling. Forge tooling helps agents inspect capability gaps and build least-privilege capsules for new functions. -
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AgentENV
Distributed platform for running agent environments at scale
AgentENV is a distributed platform for running large numbers of isolated AI-agent environments across one or more machines. It uses Firecracker microVMs to provide strong sandboxing while loading diverse OCI-compatible images on demand. Overlay-based storage and bounded local caching keep frequently used data close without requiring every image to fit on each host. Snapshot-backed sandboxes can pause, resume, fork, and persist memory and filesystem changes for parallel or recoverable workflows. The platform includes an aenv command-line interface for creating templates, starting shells, executing commands, and managing sandbox lifecycles. Its E2B-compatible HTTP API lets existing Python and TypeScript integrations target a self-hosted deployment with minimal changes. AgentENV is designed for high-density agentic reinforcement learning and currently requires trusted-network deployment because built-in authorization is not yet available. -
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Chidori
A reactive runtime for building durable AI agents
A reactive runtime for building durable AI agents. Chidori is an open-source orchestrator, runtime, and IDE for building software in symbiosis with modern AI tools. When using Chidori, you author code with python or javascript, we provide a layer for interfacing with the complexities of AI models in long-running workflows. We have avoided the need for declaring a new language or SDK in order to provide these capabilities so that you can leverage software patterns that you are already familiar with. -
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CubeSandbox
Instant, Concurrent, Secure & Lightweight Sandbox for AI Agents
CubeSandbox is a lightweight, high-performance sandboxing environment designed to securely run AI agents and untrusted code in isolated containers. Built in Rust, it focuses on enabling concurrent execution while maintaining strong isolation and low overhead. The system is optimized for scenarios where multiple AI agents need to execute tasks in parallel without compromising system integrity. It provides fast startup times and efficient resource management, making it suitable for large-scale agent orchestration. CubeSandbox integrates well with cloud-native workflows and modern infrastructure pipelines. Its design prioritizes security, concurrency, and performance in AI-driven environments. It is particularly useful for agent frameworks requiring safe execution of generated code. -
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Moltis
A Rust-native claw you can trust
Moltis is an open-source personal AI assistant platform written in Rust that is designed to run as a fully self-hosted, local-first agent environment. It compiles the entire assistant stack, including the web interface, model routing, memory, and tools, into a single self-contained binary with no external runtime dependencies. The system supports multiple large language model providers alongside local models, enabling users to maintain privacy while still accessing cloud capabilities when needed. Moltis emphasizes security through sandboxed execution environments, where commands and browsing tasks run in isolated containers and require explicit approval. The platform also includes long-term memory powered by hybrid vector and full-text search, allowing the assistant to retain context across sessions. With multi-channel access such as web UI, Telegram, and API endpoints, Moltis functions as a unified automation hub intended for developers and advanced users who want full control. -
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Phantasm
Toolkits to create a human-in-the-loop approval layer
Phantasm offers toolkits to create a human-in-the-loop approval layer to monitor and guide AI agents' workflows in real-time, ensuring safety and reliability in AI operations. -
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Rewriting Project Claw Code
Ensure consistency and alignment between different codebases
Rewriting Project Claw Code is a development tool or framework designed to ensure consistency and alignment between different codebases, environments, or implementations. It focuses on maintaining parity across systems, which is particularly important in distributed architectures or multi-platform applications. The project provides mechanisms to compare, validate, and synchronize code or behavior, helping teams avoid discrepancies that can lead to bugs or inconsistencies. It may include automation tools that detect differences and enforce standards across repositories. The tool is useful in scenarios such as maintaining parity between frontend and backend logic, ensuring API consistency, or synchronizing multiple deployments. Its design promotes reliability and reduces the risk of divergence in complex systems. Overall, Claw Code Parity helps teams maintain cohesion across their codebases while improving development efficiency and quality assurance. -
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Rust Port
The Rust workspace under rust/ is the current systems-language port
Rust Port is an open-source reconstruction and experimentation framework derived from leaked or reverse-engineered versions of advanced AI coding agents, designed to replicate and extend the capabilities of agentic development systems. It functions as a programmable coding assistant that operates through autonomous workflows, enabling users to generate, modify, and analyze code with minimal manual intervention. The project emphasizes agent-based execution, where tasks are broken down into steps and handled iteratively, simulating how modern AI coding tools operate in production environments. It is often used as a sandbox for exploring how large-scale coding agents behave, including their decision-making processes, tool usage, and workflow orchestration. The system likely includes abstractions for handling file systems, executing commands, and maintaining context across sessions, allowing for more persistent and intelligent coding interactions. -
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best-claude-hud
Minimal Claude Code statusline HUD powered by Rust
best-claude-hud is a fast Rust-based status line for Claude Code terminal sessions. It displays the active model, available reasoning effort, launch directory, Git state, and context-window consumption in a compact interface. Optional segments can also show usage limits, cost, session details, output style, and update information. The npm package installs prebuilt native binaries, so users do not need a Rust toolchain. Its setup command updates Claude Code settings, preserves existing configuration, and creates a backup when replacing a previous status line. A terminal interface supports configuration, built-in themes, custom themes, model aliases, and custom context limits. The project supports major macOS, Linux, and Windows desktop architectures and avoids unnecessary Git locking while collecting repository status. -
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forkd
Fork() for AI agent microVMs
forkd is a microVM sandbox runtime designed for high-speed AI agent fan-out. Instead of cold-booting a separate virtual machine for every worker, it forks children from a warmed parent snapshot and uses copy-on-write behavior to share the initial memory state. This makes it useful for spawning many isolated agent environments quickly during parallel research, testing, or code execution. The project is focused on runtime performance, sandbox isolation, and efficient branching from a live or prepared VM state. It is especially relevant for developers building agent infrastructure where many short-lived execution branches need to run safely. forkd is best understood as a low-level systems tool for scalable, isolated AI-agent workloads.
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