Open Source Rust Agentic AI Tools
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Rust Agentic AI Tools
View 104 business solutionsBrowse free open source Rust Agentic AI Tools and projects below. Use the toggles on the left to filter open source Rust Agentic AI Tools by OS, license, language, programming language, and project status.
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
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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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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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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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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. -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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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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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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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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OpenFang
Open-source Agent Operating System
OpenFang is an open-source agent operating system designed to orchestrate autonomous AI agents and workflows in a structured, production-oriented environment. Written primarily in Rust, the project focuses on building a high-performance runtime where multiple specialized agents can collaborate to complete complex computational or development tasks. It aims to move beyond simple chat-based agents by providing infrastructure for persistent agent memory, task coordination, and scalable execution. The system is positioned as a foundation for building advanced AI tooling, particularly in environments that require tight integration with GPU workflows and modern AI pipelines. OpenFang emphasizes modularity and extensibility so developers can plug in custom agents, tools, or execution backends. Overall, the project represents an emerging class of “agent OS” platforms that treat AI agents as first-class computational actors rather than isolated scripts. -
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OpenShell
OpenShell is the safe, private runtime for autonomous AI agents.
OpenShell is an open-source runtime designed to safely run autonomous AI agents in isolated environments. Developed by NVIDIA, it provides sandboxed execution spaces that protect system resources, credentials, and data from unauthorized access. Each agent runs inside a containerized sandbox governed by declarative YAML security policies that control network access, file permissions, and process behavior. The platform includes a gateway service that manages sandbox lifecycles and routes AI inference requests through controlled providers. OpenShell also features a privacy-aware routing system that prevents sensitive information from leaving the sandbox environment. By combining container isolation, policy enforcement, and agent orchestration, OpenShell offers a secure infrastructure for developing and operating AI agents. -
99.99% Uptime for MySQL and PostgreSQL DatabasesCloud SQL Enterprise Plus delivers near-zero downtime with 35 days of point-in-time recovery. Supports MySQL, PostgreSQL, and SQL Server.
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Claw Code
AI agent harness for AI coding agents
Claw Code is an open-source AI agent harness project focused on building better tools for orchestrating and managing autonomous coding agents. It originated as a clean-room reimplementation inspired by the architecture of Claude Code, aiming to replicate core concepts without using proprietary code. The project provides a Python-based foundation for experimenting with agent workflows, tool integration, and task execution pipelines. It emphasizes harness engineering—how agents are structured, how they interact with tools, and how they maintain context during execution. The system is being actively expanded, with a Rust-based runtime in development to improve performance and memory safety. Overall, Claw Code serves as a research-driven platform for advancing agent-based software development systems. -
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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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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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Google Workspace CLI
Command-line tool for Drive, Gmail, Calendar, Sheets, Docs, Chat, etc.
Google Workspace CLI (gws) is a command-line tool designed to interact with Google Workspace services such as Drive, Gmail, Calendar, Sheets, and more from a single interface. It dynamically generates its command structure using Google’s Discovery Service, allowing it to automatically support new API endpoints as they become available. The tool eliminates the need for manual REST API calls by providing structured commands and built-in help for each resource and method. It outputs structured JSON responses, making it easy for developers, scripts, and AI agents to process results programmatically. The CLI supports multiple authentication methods, including OAuth login, service accounts, and environment-based credentials for automated environments. With built-in agent skills and automation features, it enables developers and AI systems to manage and automate Google Workspace workflows efficiently. -
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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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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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Coral
One SQL interface over APIs, files, and live sources
Coral is a local-first SQL runtime that lets agents query APIs, files, and live data sources through a single interface. It is designed to make external data easier for AI agents to inspect, structure, and use without requiring a different integration pattern for every service. The project gives developers a command-line workflow for querying data, inspecting schemas, and working with tables. It is especially useful for agentic systems that need reliable access to context from multiple sources while keeping the runtime close to the developer’s environment. Coral focuses on composability, so different data sources can be treated as part of a shared query layer. Its main value is giving AI workflows a practical database-like abstraction over messy external information. -
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Tokscale
A CLI tool for tracking token usage from OpenCode, Claude Code
Tokscale is a CLI and terminal UI tool that tracks token usage and estimated cost across multiple AI coding assistants and development workflows. It treats tokens like a measurable resource, helping developers understand how much “AI energy” they are consuming over time and where it is being spent. The tool aggregates usage across supported platforms and presents it through interactive views that let users filter, sort, and explore trends without leaving the terminal. Tokscale also includes rich visualizations such as contribution-graph style summaries and daily breakdowns, making it easy to spot spikes, habits, and long-term patterns. For cost estimation, it can map usage to pricing data so developers can see what their activity implies financially across different models. -
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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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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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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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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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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.