I’ve been building tooler, an open-source runtime written in Rust designed to give developers, DevOps workflows, and AI agents a consistent set of real-world tools.
Instead of letting an agent rely on arbitrary shell commands, tooler provides structured capabilities for HTTP requests, databases, filesystems, processes, logs, Git/GitHub, deployments, health checks, systemd, cron, remote hosts, and reusable playbooks.
It also exposes its capabilities through MCP, making them directly accessible to AI agents.
The idea is simple:
LLM → reasoning and planning → tooler → deterministic execution
This creates a clean separation between what the agent decides to do and how those operations are safely and consistently executed.
tooler is built in Rust, distributed as a standalone binary, and designed for both humans and AI agents.
In this post, I’ll introduce the project, its architecture, why I built it, and how I’m exploring tooler as an execution layer for increasingly complex agentic workflows.