Hey everyone!

I'm excited to share ADK-Rust - a production-ready implementation of Google's Agent Development Kit in Rust.

Why Rust? After working extensively with adk-python in developing an ai agent factory at zavora.ai, I wanted to bring the same powerful agent development patterns to the Rust ecosystem, targeting use cases where:

Performance is critical - Rust's zero-cost abstractions and memory safety Deployment size matters - Single binary with no runtime dependencies Systems-level integration - Embedded systems, edge computing, IoT Concurrency at scale - Rust's async/await with tokio Features ADK-Rust maintains API parity with the Python ADK where possible:

Model-agnostic - Gemini, OpenAI, Anthropic, DeepSeek support Multiple agent types - LlmAgent, SequentialAgent, ParallelAgent, LoopAgent Tool support - Built-in tools (Google Search, Code Execution) + custom tools MCP support - Model Context Protocol integration Sessions & Memory - InMemorySessionService, DatabaseSessionService Streaming - Full streaming support for real-time responses Telemetry - OpenTelemetry integration for tracing/metrics A2A Protocol - Agent-to-Agent communication

Quick Example

use adk_rust::prelude::*;

#[tokio::main] async fn main() -> Result<()> { let agent = LlmAgentBuilder::new() .name("my_agent") .model(GeminiModel::new("gemini-2.0-flash")?) .instruction("You are a helpful assistant.") .build()?;

    let response = agent.run("Hello!").await?;
    println!("{}", response);
    Ok(())

}

Links Crates.io: https://crates.io/crates/adk-rust Docs: https://docs.rs/adk-rust Website: https://adk-rust.com/ GitHub: https://github.com/zavora-ai/adk-rust Looking for Feedback I'd love to hear from the community:

What agentic features would you prioritize? Any interest in contributing or testing? Use cases where a Rust implementation would be valuable? This is an independent community project, not officially affiliated with Google, but designed to be compatible with the ADK ecosystem.

Thanks for reading!