Open Source BSD AI Agents
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AI Agents for BSD
Browse free open source AI Agents and projects for BSD below. Use the toggles on the left to filter open source AI Agents by OS, license, language, programming language, and project status.
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Claude Code
Claude Code is an agentic coding tool that lives in your terminal
Claude Code is an intelligent agentic coding assistant that lives in your terminal and understands your entire codebase. It helps developers code faster by executing routine tasks, explaining complex code snippets, and managing git workflows—all via natural language commands. Claude Code integrates seamlessly into your terminal, IDE, or GitHub by tagging @claude to interact with your code context. The tool is designed to simplify development by automating repetitive work and providing instant clarifications on code behavior. User feedback and usage data are collected responsibly, with strict privacy safeguards and limited retention, ensuring no feedback is used to train generative models. Claude Code is open and actively maintained with community-driven bug reporting and feature requests. Its natural language interface makes advanced coding workflows accessible without leaving your coding environment. -
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Grok CLI
An open-source AI agent that brings the power of Grok
Grok CLI is a command-line interface built around the Grok AI model that brings programmatic and conversational AI capabilities directly to developer terminals. It lets you run Grok queries from your shell, scripting environment, or automation workflows without switching to a browser, enabling utility in scripting, quick data exploration, code generation, and assistant-guided tasks directly where you write code. The CLI supports streaming responses, so outputs appear in real time as the Grok model generates them, making interactions feel responsive and fluid in terminal contexts. Grok CLI is designed to integrate with existing terminal habits—aliases, pipes, editors, and tooling—so you can combine AI assistance with native command-line workflows like grep, awk, and git. It also includes authentication support, configuration management, and caching options so frequent queries are efficient. -
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OpenManus
Open-source AI agent framework
OpenManus is an open-source AI agent framework designed to autonomously execute complex, multi-step tasks by combining reasoning, planning, and tool use. It enables developers to build agents that can think, act, and iterate toward goals rather than simply responding to prompts. The platform emphasizes task decomposition, allowing agents to break down objectives into smaller steps and execute them sequentially or recursively. OpenManus supports integration with external tools, APIs, and environments, making it suitable for real-world automation workflows. It is built to be flexible and extensible, enabling customization of agent behaviors, tools, and reasoning strategies. Overall, OpenManus provides a foundation for creating more capable, autonomous AI systems that can handle dynamic and goal-driven tasks. -
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Paperclip
Open-source orchestration for zero-human companies
Paperclip is an open-source tool designed to help AI systems and developer tools access academic research papers through a standardized interface. The project implements a server based on the Model Context Protocol (MCP), a framework that allows large language models and AI agents to connect to external data sources and tools in a consistent way. By acting as a middleware layer, Paperclip aggregates multiple academic databases and exposes them through a single interface, allowing AI applications to search and retrieve scholarly papers without needing to integrate with each provider individually. The system supports repositories such as arXiv, OpenAlex, and the Open Science Framework, giving AI agents access to a large body of research literature. Instead of requiring separate APIs and authentication flows for each service, Paperclip provides unified search and retrieval capabilities that simplify integration into AI workflows. -
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OpenAI Python
The official Python library for the OpenAI API
The OpenAI Python library provides convenient access to the OpenAI REST API from any Python 3.7+ application. The library includes type definitions for all request params and response fields, and offers both synchronous and asynchronous clients powered by httpx. -
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Alan AI
In-App assistant SDK to build a multimodal conversational UX websites
Quickly add voice to your app with the Alan Platform. Create an in-app voice assistant to enable human-like conversations and provide a personalized voice experience for every user. Alan is a conversational voice AI platform that lets you create an intelligent voice assistant for your app. It offers all the necessary tools to design, embed, and host your voice solutions. A powerful web-based IDE where you can write, test and debug dialog scenarios for your voice assistant or chatbot. Alan's AI-backend powered by the industry’s best Automatic Speech Recognition (ASR), Natural Language Understanding (NLU) and Speech Synthesis. The Alan Cloud provisions and handles the infrastructure required to maintain your voice deployments and perform all the voice processing tasks. To voice enable your app, you only need to get the Alan Client SDK and drop it to your app. No need to plan for, deploy and maintain any infrastructure or speech components - the Alan Platform does the bulk of the work. -
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Poco Claw
A more beautiful and easier-to-use alternative to OpenClaw
Poco Claw is an AI agent platform designed as a more user-friendly and visually polished alternative to traditional OpenClaw implementations. It focuses on improving usability by providing a modern web interface combined with enhanced interaction capabilities such as built-in messaging and project organization tools. The system operates on a sandboxed runtime, ensuring that tasks executed by the agent are isolated from the host environment, which improves security and reliability. It extends beyond simple chatbot functionality by supporting structured workflows, task planning modes, and multi-step execution pipelines. The platform also allows users to manage files and contexts directly within the interface, enabling more complex interactions with data and projects. It is built to make AI agent systems accessible to a broader audience, including users who may not be comfortable with command-line environments. -
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Agent Skills
Skills for AI coding agents
Agent Skills by Vercel Labs is a curated collection of modular “skills” designed to extend the capabilities of AI coding agents by packaging human-ready instructions, workflows, and optional scripts that tell an agent how to perform specific development tasks. In this repository, each skill adheres to the Agent Skills specification, meaning they’re defined as folders with a SKILL.md file (containing task descriptions and step-by-step guidance) and can include helper scripts and reference material that the agent can execute or consult when invoked. The goal of the project is to make it easy for AI assistants like Claude Code, OpenCode, Cursor, Codex, and others that support this open ecosystem to automatically apply best practices or perform concrete actions when a relevant user intent is detected. For example, some skills guide the agent in applying React and Next.js performance best practices, auditing UI and accessibility standards. -
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PenEcho
Think with AI beyond the chat box
PenEcho is an open-source shared canvas that makes handwriting, equations, diagrams, and spatial context part of an AI conversation. Users can draw with pressure-sensitive ink, erase, pan, zoom, type formatted text, and arrange ideas across a large virtual workspace. The application sends focused visual regions to an API, Codex CLI, or Claude CLI and converts model responses into editable canvas commands. AI output can include text, formulas, plots, mixed drawings, erasures, and declarative animations. Sparse tile rendering keeps the 20,000-by-20,000 logical canvas efficient without allocating one enormous bitmap. Local snapshots, undo and redo, lasso selection, PNG export, and manual or automatic AI modes support iterative work. PenEcho is available as a desktop application or Node.js package and supports configurable models, reasoning levels, request retention, and plugins. -
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AGI
The first distributed AGI system
AGI project is an experimental framework focused on building components and infrastructure for artificial general intelligence systems, emphasizing modularity, autonomy, and scalable intelligence pipelines. It aims to provide a foundation for creating agents that can reason, plan, and execute tasks across diverse domains by integrating multiple AI capabilities into a unified system. The project typically explores concepts such as agent orchestration, memory systems, task decomposition, and decision-making loops, enabling the development of more generalized and adaptive AI behaviors. It is designed to be extensible, allowing developers to plug in different models, tools, and data sources to enhance agent performance. The framework encourages experimentation with AGI-like architectures, making it useful for researchers and developers interested in advancing beyond narrow AI applications. -
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500+ AI Agent Projects
The 500 AI Agents Projects is a curated collection of AI agent
500 AI Agents Projects is a curated repository that aggregates hundreds of real-world AI agent use cases across multiple industries, serving as a centralized knowledge hub for developers, researchers, and businesses. Rather than being a single application, it functions as a structured index linking to open-source implementations and conceptual examples of agent-based systems. The repository highlights how AI agents can be applied in domains such as healthcare, finance, education, and retail, offering inspiration and practical entry points for building solutions. It simplifies exploration by organizing diverse projects into a single accessible location, making it easier to discover trends and patterns in agentic AI development. The project encourages collaboration and contributions, positioning itself as a living resource that evolves with the ecosystem. Its value lies in breadth, discoverability, and practical orientation toward implementation. -
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OpenConnector
Open-source auth gateway connecting 1000+ SaaS providers to AI agents
OpenConnector is an open-source integration gateway that gives AI agents controlled access to external applications and services. It exposes a shared catalog of more than 1,000 providers and over 10,000 predefined actions. Applications can call those actions through a TypeScript SDK, command-line relay, MCP, HTTP endpoints, or generated OpenAPI specifications. The runtime manages OAuth, API keys, custom credentials, scopes, tokens, policies, temporary files, and redacted logs. A web console helps administrators browse connectors, configure accounts, create runtime tokens, and inspect activity. It can run locally with Node.js or Docker, on Fly.io, on Cloudflare-compatible infrastructure, or through OOMOL's hosted environment. Its main purpose is to keep provider credentials outside agent processes while maintaining inspectable and reusable access contracts. -
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Taste Skill
Taste-Skill - gives your AI good taste. stops the AI
Taste Skill is a project focused on structured skill development, likely combining curated content, learning paths, and interactive elements to help users build expertise in specific domains. It appears to emphasize personalized or modular learning, allowing users to explore topics based on interest or progression level. The platform may integrate recommendation systems or categorized content to guide users through a learning journey efficiently. Its design suggests an emphasis on accessibility and practical skill acquisition rather than purely theoretical knowledge. The repository likely includes tools or interfaces that support content organization, tracking, and user engagement. Overall, it positions itself as a lightweight, adaptable system for continuous learning and skill discovery. -
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ASu-skills
Job-search workflow plugin suite
ASu-skills is a job-search workflow plugin suite designed for AI coding assistants. It provides specialized entry points for building verifiable experience, improving resume content, creating resumes, preparing for interviews, and tracking applications. Its contributor workflow helps users identify realistic open-source contributions and prepares changes for approval before submission. Resume tools can rewrite experience for target roles and generate editable HTML layouts with PDF export. Interview workflows analyze resume claims, predict likely questions, and probe knowledge gaps through follow-up questions. The suite supports Claude Code, Codex, and TraeWork while sharing common skills, assets, and reference materials. -
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OpenSandbox
OpenSandbox is a general-purpose sandbox platform for AI applications
OpenSandbox is a general purpose sandbox platform designed to securely run and isolate AI applications and untrusted workloads in controlled environments. The project focuses on providing a unified sandbox API that simplifies the process of executing code safely across different runtime backends. It supports multiple programming languages through SDKs, allowing developers to integrate sandbox capabilities into their systems without building custom isolation layers. The platform is built to work with container technologies such as Docker and Kubernetes, enabling scalable and production ready deployments. OpenSandbox is particularly useful for AI agents, code execution services, and any scenario where untrusted code must be executed safely. Its architecture emphasizes flexibility, security boundaries, and operational consistency across environments. Overall, the project aims to standardize sandbox execution for modern AI and cloud native workflows. -
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Cloudflare OS
Agent workspace built on Cloudflare Workers for creating documents
Cloudflare OS is an open-source AI productivity environment originally developed for internal use across Cloudflare. It combines an agent chat interface, company-specific knowledge, sandboxed application creation, and a capability-based security framework. Users can ask agents to prepare documents, build dashboards, create collaborative tools, or work with connected services. Generated applications are called Gadgets and run as private, isolated instances that can be modified and securely shared. Gatekeepers control external access, manage authorization, log actions, restrict resources, and queue side effects for later human approval. Blueprints serve as reusable application templates rather than simple document templates. The system runs on Cloudflare Workers and is released as an early-access foundation that organizations can customize into their own company operating environment. -
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MiMo Code
Where Models and Agents Co-Evolve
MiMo-Code is a terminal-native AI coding assistant built for real software projects. It can read and edit code, run commands, manage Git, and preserve project knowledge across sessions. The tool includes multiple agent modes, including a build mode for development, a plan mode for read-only analysis, and a compose mode for structured workflows. Its persistent memory system stores project notes, checkpoints, scratch notes, and task progress so the assistant can resume work with context. It also supports subagents, goal checking, voice input, MCP connections, and custom provider configuration. MiMo-Code is useful for developers who want an autonomous coding assistant that combines terminal workflows, long-running task management, and project-aware memory. -
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AutoGen
An Open-Source Programming Framework for Agentic AI
AutoGen is an open-source programming framework for building AI agents and facilitating cooperation among multiple agents to solve tasks. AutoGen aims to provide an easy-to-use and flexible framework for accelerating development and research on agentic AI, like PyTorch for Deep Learning. It offers features such as agents that can converse with other agents, LLM and tool use support, autonomous and human-in-the-loop workflows, and multi-agent conversation patterns. AutoGen provides multi-agent conversation framework as a high-level abstraction. With this framework, one can conveniently build LLM workflows. AutoGen offers a collection of working systems spanning a wide range of applications from various domains and complexities. AutoGen supports enhanced LLM inference APIs, which can be used to improve inference performance and reduce cost. -
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Utopia
World's first open-source enterprise world model
Utopia is an open-source enterprise world model designed to turn evolving organizational knowledge into a governed decision layer. It combines a bitemporal knowledge graph, editable ontology, retrieval, reasoning, and audit history in one self-hosted application. The system ingests documents and synchronized sources, then extracts entities and facts with provenance and validity intervals. Corrections preserve earlier versions instead of overwriting them. Hybrid search and chat work across documents and mounted databases through OpenAI-compatible models. Temporal Datalog rules derive new facts, while conflict detection and review queues surface contradictions or uncertain merges. Role-based permissions and a decision ledger make changes traceable for enterprise use. -
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AI-Trader
100% Fully-Automated Agent-Native Trading
AI-Trader is an open-source AI-powered quantitative trading framework designed to combine financial analysis, machine learning, and autonomous trading workflows into a unified research platform. The project integrates large language models, financial indicators, market analysis pipelines, and automated decision-making systems to support strategy generation and market prediction tasks. It is built to help researchers and developers experiment with AI-assisted trading strategies using historical and real-time financial data. The framework supports modular components for portfolio analysis, signal generation, market reasoning, and trading automation, allowing users to customize workflows for different trading styles and asset classes. AI-Trader also emphasizes extensibility for integrating external APIs, datasets, and custom models. -
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Antigravity Kit
AI Agent templates with Skills, Agents, and Workflows
Antigravity Kit is an AI agent capability expansion toolkit that provides structured templates, skills, and workflows designed to boost the productivity of AI assistants and autonomous agents in coding environments. It comes with an extensive library of predefined agent personas and domain-specific skills that help in performing targeted tasks such as frontend development, backend engineering, quality assurance, and more. With this kit, developers can rapidly initialize a project scaffold and gain access to specialist agents and command workflows that guide the agent through multi-step tasks and slash-command procedures. The repository follows a clear pattern for defining agents and their behaviors, making it easier to extend with new skills or tailor existing ones to your use case. Because it’s framework-agnostic at its core, the Antigravity Kit can integrate with IDEs and other development tooling for smoother AI-augmented coding. -
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Cangjie Skill
Distill high-value content like books, long videos, podcasts, and more
cangjie-skill is a workflow for converting books and other long-form knowledge into executable AI skill packs. Its goal is structured reuse rather than producing another summary or set of reading notes. The seven-stage RIA-TV++ pipeline analyzes the full source, extracts candidate frameworks, verifies them, constructs skill modules, links related ideas, pressure-tests behavior, and prepares delivery files. Each accepted skill records supporting material, a reconstructed explanation, examples, trigger situations, executable steps, and limitations. Strict verification rejects generic or weak ideas that lack independent evidence, predictive value, or meaningful uniqueness. The generated package can include an overview, glossary, reference graph, long-form digest, individual skill files, and test prompts. Completed skills can be installed for compatible coding agents such as Claude Code and Cursor. -
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ClawTeam
ClawTeam: Agent Swarm Intelligence (One Command → Full Automation)
ClawTeam is an advanced multi-agent orchestration framework that enables AI agents to form collaborative swarms capable of solving complex tasks autonomously. Instead of relying on a single agent, the system allows a leader agent to spawn and coordinate multiple specialized sub-agents, each responsible for different aspects of a problem. These agents communicate, share insights, and dynamically adapt their strategies based on real-time feedback, creating a form of collective intelligence. The framework supports a wide range of use cases, including software development, machine learning research, financial analysis, and content production. It is designed to work with various AI tools and command-line agents, making it highly flexible and extensible. ClawTeam also includes monitoring tools such as dashboards and tmux-based views to observe agent activity and progress. -
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agents.md
A simple, open format for guiding coding agents
openai/agents.md is a repository whose primary file is AGENTS.md, a proposed open, lightweight convention (i.e. Markdown file) for guiding coding agents in software repositories. The idea is that AGENTS.md acts as a “README for agents”: a predictable, structured place where humans can put instructions, conventions, build/test commands, environment setup, and other guidance that generative agents (e.g. code-writing, code-assisting tools) should consult when operating in the repo. Instead of putting everything in README or doc files (which are more human-oriented and might mix high-level narrative), AGENTS.md is intended to surface agent-relevant details that help them “do the right thing” (tests, style, project structure, tooling). -
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img2threejs
Rebuild the object in a reference image as a code-only, procedural
img2threejs is an open-source agent skill that rebuilds an object from one reference image as procedural Three.js code. It generates a TypeScript THREE.Group factory from primitives, procedural shaders, and generated geometry rather than extracting or downloading a mesh. The resulting hierarchy can include pivots, sockets, colliders, and destruction groups so the model is ready for interaction and animation. A staged pipeline evaluates suitability, defines a detailed specification, builds successive passes, renders browser previews, and compares them with the source image. Quality gates require structural detail, material realism, correct attachments, and passing visual-review scores. The system can classify objects, characters, and hybrid subjects, with specialized reconstruction paths for each. It works with Claude Code, Codex, or OpenCode and can refine its specification or code when a review fails.
