I’ve been working on ADK-Rust, an open-source framework for building and deploying AI agents in Rust.
The motivation came from building agent systems where performance, safety, and predictable behavior mattered more than rapid prototyping. Most agent frameworks and workflow tools today are Python- or JS-first and tend to be runtime-heavy when taken to production.
Recently, I added ADK-Studio — a visual, low-code environment for building AI agent workflows on top of ADK-Rust.
You can think of ADK-Studio as a Rust-native alternative to tools like n8n, but focused specifically on AI agents:
- Visual, drag-and-drop workflow design (sequential, parallel, loop, router agents)
- Tool integration (functions, MCP servers, browser automation, search)
- Real-time execution with SSE streaming and event traces
- Code generation: visual workflows compile down to production Rust code
- Build and run agents as native executables directly from the studio
The goal is to let people prototype agent workflows visually, then ship them as fast, memory-safe Rust binaries instead of long-running JS/Python services.
Making AI Agents with ADK Studio is super simple:
1. ADK-Studio install: `cargo install adk-studio`
2. Start ADK Studio server: `adk-studio --port 6000`
3. Open in browser: open http://localhost:6000
I would really appreciate feedback from folks building agent systems, workflow engines, or AI inference infrastructure — especially around design tradeoffs vs existing tools like n8n.
I’ve been working on ADK-Rust, an open-source framework for building and deploying AI agents in Rust.
The motivation came from building agent systems where performance, safety, and predictable behavior mattered more than rapid prototyping. Most agent frameworks and workflow tools today are Python- or JS-first and tend to be runtime-heavy when taken to production.
Recently, I added ADK-Studio — a visual, low-code environment for building AI agent workflows on top of ADK-Rust.
You can think of ADK-Studio as a Rust-native alternative to tools like n8n, but focused specifically on AI agents: - Visual, drag-and-drop workflow design (sequential, parallel, loop, router agents) - Tool integration (functions, MCP servers, browser automation, search) - Real-time execution with SSE streaming and event traces - Code generation: visual workflows compile down to production Rust code - Build and run agents as native executables directly from the studio
The goal is to let people prototype agent workflows visually, then ship them as fast, memory-safe Rust binaries instead of long-running JS/Python services.
Making AI Agents with ADK Studio is super simple:
1. ADK-Studio install: `cargo install adk-studio` 2. Start ADK Studio server: `adk-studio --port 6000` 3. Open in browser: open http://localhost:6000
I would really appreciate feedback from folks building agent systems, workflow engines, or AI inference infrastructure — especially around design tradeoffs vs existing tools like n8n.
Project site: https://adk-rust.com GitHub: https://github.com/zavora-ai/adk-rust
Best James