AutoDevOS runs an autonomous agentic loop — read, edit, execute, and iterate with your codebase using natural language. Supports every major LLM.

Capabilities
Built for engineers who want AI to do the heavy lifting — autonomously and securely
Autonomous multi-step loop — plan, execute tools, observe results, and iterate without manual intervention up to 100 turns.
OpenAI, Anthropic Claude, Google Gemini, Ollama, OpenRouter, LM Studio, vLLM, and any OpenAI-compatible endpoint.
Shell execution, file read/write/edit, grep, glob, web search, web fetch, memory, and TODO tracking — ready to use.
Extend capabilities with any Model Context Protocol (MCP) server via stdio or HTTP/SSE transport.
Automatic conversation compression when approaching the model context window preserves task continuity.
Approval policies, blocked destructive commands, path validation, and secret-variable filtering built in.
Trigger shell scripts at before_agent, after_agent, before_tool, after_tool, and on_error events.
Save and resume conversations with full context using /save and /clear in-session commands.
Detects repeated identical tool calls and injects a circuit-breaker to prevent runaway loops.
Supported LLM Providers
Workflow
Install via pip or pipx, then run the interactive auth wizard to connect your preferred LLM provider and store your API key securely.
Navigate to any codebase. The agent reads your project context, AGENTS.md instructions, and project-level config automatically.
Describe a task in plain English. The agent reads your code, makes edits, runs commands, and verifies results autonomously.
Built-in Toolkit
The agent picks the right tool for every step automatically — no configuration needed
In Action

Community
AutoDevOS completely changed how I develop. It's like having a senior engineer always available.
Alex Chen
Full Stack Developer
The agentic loop is incredible — I give it a task and come back to it done. No hand-holding needed.
Sarah Williams
Software Engineer
Finally an AI terminal tool that lets me use local Ollama models for privacy-sensitive work.
Mike Johnson
DevOps Engineer
Install AutoDevOS and let the agent handle the repetitive work so you can focus on what matters.