Ouroboros 0.26.0-beta Combines Claude and Codex via MCP Server
Multi-AI Orchestration Tool Released
Ouroboros 0.26.0-beta is a tool that runs Claude and Codex together, assigning each AI a specific role rather than forcing developers to choose one model. The system uses Claude for intent clarification and Codex for execution, connected through an MCP server architecture.
Architecture and Workflow
The tool functions as a harness where Claude handles the "interview" phase: it asks questions until user intent is clear, requiring an ambiguity score below 0.2 before proceeding. Claude's long context and deep reasoning capabilities make it suitable for this clarification role.
Once intent is established, Codex takes over execution. Codex operates autonomously on well-defined acceptance criteria without overthinking, focusing on fast implementation.
Technical Implementation
The key component is the MCP (Model Context Protocol) layer. Ouroboros runs as an MCP server, allowing any runtime to call into it—Claude, Codex, or both. The orchestration logic resides in the server rather than in the CLI, creating a modular architecture.
This server-based approach means workflows remain consistent when swapping out either model. Developers can select the appropriate model for each specific job without being locked into a single AI.
The latest version 0.26.0-beta includes full Codex support. The project is available at github.com/Q00/ouroboros.
📖 Read the full source: r/ClaudeAI
👀 See Also
SkyClaw: Rust-Based Autonomous AI Agent Runtime
SkyClaw is an autonomous AI agent runtime built in Rust with a 7.1 MB binary that idles at 14 MB RAM and starts in under one second. It operates on five engineering principles including autonomy, robustness, and brutal efficiency.
Parallel Agent Orchestrator for Claude Code Using Git Worktrees
A developer built a parallel orchestrator that uses git worktrees to create isolated environments for Claude Code agents, solving the problem of shared working directories causing broken apps and messy git status.
AIMEAT: A Self-Hosted Protocol for AI Agents, Local LLMs, and Shared Capabilities
AIMEAT is a self-hosted protocol and server that lets humans, AI agents, and local LLMs share apps, knowledge, and capabilities over HTTP/JSON. No vendor lock, no special SDK — plain prompts and URL fetches.
Needle: A 26M Parameter Tool-Calling Model Built Entirely Without FFNs
Needle is a 26M parameter function-calling model with no MLPs, achieving 6000 tok/s prefill and 1200 tok/s decode on consumer devices. It beats FunctionGemma-270M, Qwen-0.6B, Granite-350M, and LFM2.5-350M on single-shot tool calling.