Q00/ouroboros
by Various
Agent OS: the agent gets smarter on its own. We just hold the line: Interview-gated, staged evaluation, budgeted evolution loop. MCP server, 14 runtimes: Claude Code, Codex CLI, Ge
MCP
Q00/ouroboros
Added 8 Sept 2026
Overview
Q00/ouroboros is an Agent OS that enables agents to improve themselves through an interview-gated, staged evaluation process with a budgeted evolution loop. It operates as an MCP server and supports 14 runtimes including Claude Code, Codex CLI, Gemini CLI, OpenCode, Copilot, and Kiro. Written in Python, it is open-source with over 5,700 stars.
Best for
Best for
Developers building self-improving AI agents across multiple CLI environments.
Use cases
- Automate agent self-improvement pipelines
- Evaluate agent performance across multiple CLI runtimes
- Integrate MCP-based agent orchestration into existing workflows
How to use
Install
pip install 'ouroboros-ai[mcp,tui]' && ouroboros setup --runtime claude-cli # recommended MCP v2 default Tested with
Claude Code, Continue, ChatGPT
Notes
Q00/ouroboros is an Agent OS that enables agents to improve themselves through an interview-gated, staged evaluation process with a budgeted evolution loop. It operates as an MCP server and supports 14 runtimes including Claude Code, Codex CLI, Gemini CLI, OpenCode, Copilot, and Kiro. Written in Python, it is open-source with over 5,700 stars.
5,799 stars on GitHub. Last updated 2026-09-08. Licensed MIT.
Use cases
- Automate agent self-improvement pipelines
- Evaluate agent performance across multiple CLI runtimes
- Integrate MCP-based agent orchestration into existing workflows
Pros
- Broad runtime compatibility with 14 supported tools
- Self-improving architecture with staged evaluation
- Active open-source project with 5.8k stars
Cons
- Requires Python environment and MCP setup
- Evolution loop may need careful budget tuning
- Not a standalone agent, depends on external runtimes
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Broad runtime compatibility with 14 supported tools
- Self-improving architecture with staged evaluation
- Active open-source project with 5.8k stars
Cons
- Requires Python environment and MCP setup
- Evolution loop may need careful budget tuning
- Not a standalone agent, depends on external runtimes
Open-source & AI alternatives
Swap-in tools that solve the same job. Weigh the trade-offs before you commit.
Pairs with
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