Inspiration Dulus was born from a simple frustration: every AI tool was either too limited (closed SaaS) or too hard to use (raw APIs, complex SDKs). We wanted something that just works — install via pip, run a command, and have a fully capable AI agent with access to 100+ tools, 2000+ MCP servers, and 60,000+ skills. Named after the Cigua Palmera (our national bird 🇩🇴), Dulus represents freedom, adaptability, and reaching higher.
What it does Dulus is a Python-native AI harness that transforms any LLM into a super-powered agent:
Auto-Adapter: Drop any Python repo into Dulus and it becomes a native tool automatically 104+ built-in tools: Bash, file I/O, web search, browser automation, git, tmux, image OCR, and more 2000+ MCP servers: Via the Auto-Adapter — any MCP-compatible server plugs in instantly 60,000+ skills: From Anthropic marketplace, awesome-skills catalog, and Composio (1000+ apps) Multi-agent swarms: Spawn sub-agents in isolated git worktrees for parallel coding tasks Desktop GUI: Cross-platform app with embedded terminal, file manager, browser, and chat OpenAI-compatible endpoint: Self-host with 12 frontier models, your own API keys, your rules Fleet Platform: Control Room to orchestrate agent swarms across machines $Dulus token: First utility coin usable as AI compute/quota (launching soon) How we built it Pure Python, zero dependencies for core. The architecture is modular:
Plugin system: Auto-discovers tools from any Python package via entry points Skill system: Reusable prompt templates with argument substitution MCP bridge: Native integration with the Model Context Protocol standard WebMCP support: Apps can expose tools that agents use directly on the page Nuitka builds: Compiled binaries for Windows/macOS/Linux with auto-updater Fleet server: FastAPI backend with SQLite, deployable anywhere Built in the Dominican Republic 🇩🇴 by a single developer with an army of AI allies.
Challenges we ran into Binary size vs. features: Nuitka compiles are heavy — we split into core + plugin ecosystem Cross-platform paths: Windows POSIX shell quirks, OneDrive redirections, path escaping Real-time sync: Making the desktop GUI feel native while running Python in background API costs: Built local-first with $0 API fallbacks (OCR, search, etc.) Trust: Gained by shipping for 3+ months, 90K+ PyPI downloads, real customer 911s Accomplishments that we're proud of 90,000+ PyPI downloads and counting 19,000+ MCP tools accessible via single command Auto-Adapter: Any Python repo → native Dulus tool, zero config Self-hosted endpoint: 12 frontier models, no vendor lock-in Real customers: Paying users, emergency fixes at 2AM, the whole journey Open source: GPL v3, community-driven, transparent What we learned Composition > Construction: Being clever beats being funded Local-first wins: Users love $0 API options and data ownership Speed > Perfection: Ship fast, iterate with real users AI swarms work: Divide and conquer with specialized agents What's next for Dulus $Dulus token launch: Utility coin for AI compute and platform quota Mobile app: iOS/Android harness Enterprise fleet: Multi-tenant agent orchestration More models: Integrate every frontier model as it drops Try it out pip install dulus dulus --help Or download the desktop app: github.com/Dulus-Ai/dulus-updates
Live demo: dulus.online
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