Ouroboros

v1.0.0Coding Agentsstable

Agent OS: Stop prompting. Start specifying.

agent-osai-agentmcp
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What is Ouroboros?

Ouroboros is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to agent os: stop prompting. start specifying.

Agent OS: Stop prompting. Start specifying.

This server falls under the Coding Agents category on MCPgee, the world's largest MCP server directory with 33,000+ servers.

Features

  • Agent OS: Stop prompting. Start specifying.

Use Cases

Operate an Agent OS that replaces prompting with specifications.
Stop writing prompts and start specifying agent behavior.
Q00

Maintainer

LicenseMIT
Languagepython
Versionv1.0.0
UpdatedMay 22, 2026
Statushealthy
Maintenanceactive

Works with

ClaudeOpenAIwindowsmacoslinux

Installation

Manual Installation

npx ouroboros

Configuration

Configuration Details

Config File

claude_desktop_config.json

Performance

Response Metrics

Response Time< 200ms
ThroughputMedium

Resource Usage

Memory UsageLow
CPU UsageLow

How to Set Up and Use Ouroboros

Ouroboros is an Agent OS — a local-first runtime layer for AI coding that replaces ad-hoc prompting with a structured, specification-first workflow. It guides you through a Socratic interview to crystallize requirements into an immutable seed spec, then drives AI coding agents (Claude Code, Codex CLI, GitHub Copilot CLI, Gemini, OpenCode, Kiro, and others) through execute, evaluate, and evolve stages with automated quality gates. Every action is recorded in a ledger, making agent work replayable, auditable, and policy-bound rather than one-off and non-deterministic. Developers who find AI coding sessions drift, produce inconsistent results, or require constant re-prompting will benefit from Ouroboros's structured execution contracts.

Prerequisites

  • Python 3.11 or later installed
  • pip, pipx, or uv for Python package management
  • At least one supported AI coding agent installed: Claude Code, Codex CLI, Gemini CLI, GitHub Copilot CLI, or OpenCode
  • An MCP-compatible agent host (the installer auto-registers for Claude Code, Codex, and Hermes)
1

Install Ouroboros

The quickest path is the install script, which auto-detects your AI coding agents and registers the MCP server where supported. Alternatively, install via pip or pipx.

# Quick install (auto-detects agents):
curl -fsSL https://raw.githubusercontent.com/Q00/ouroboros/main/scripts/install.sh | bash

# Or via pip:
pip install 'ouroboros-ai[claude]'

# Or via pipx:
pipx install 'ouroboros-ai[mcp]'
2

Set up your runtime

For runtimes not auto-detected (OpenCode, Kiro, GitHub Copilot CLI, Gemini, Pi), run the setup command to register the MCP server. Replace <runtime> with your agent name.

ouroboros setup --runtime opencode
# or:
ouroboros setup --runtime kiro
# or:
ouroboros setup --runtime copilot
3

Start a project with an interview

Open your AI coding agent and run the ooo interview command with a brief idea. Ouroboros will ask clarifying questions to expose hidden assumptions and produce a locked seed spec before any code is written.

ooo interview "I want to build a task management CLI in Go"
4

Execute tasks from the spec

Once the spec is crystallized, Ouroboros drives your agent through individual tasks. Each task is ledger-recorded and evaluated against the spec's acceptance criteria.

ooo execute
# or run a specific task:
ooo execute --task 1.2
5

Evaluate and evolve

After execution, Ouroboros runs its 3-stage automated evaluation gate. If quality criteria are not met, use the evolve command to refine without losing the spec context.

ooo evaluate
ooo evolve

Ouroboros Examples

Client configuration (Claude Desktop MCP)

If you need to manually register the Ouroboros MCP server in Claude Desktop:

{
  "mcpServers": {
    "ouroboros": {
      "command": "ouroboros",
      "args": ["mcp"],
      "env": {
        "OUROBOROS_RUNTIME": "claude"
      }
    }
  }
}

Prompts to try

Example ooo commands to run inside your AI coding agent after Ouroboros is set up:

- ooo interview "Build a REST API for a blog with posts, comments, and auth"
- ooo execute
- ooo evaluate
- ooo evolve
- "List all tasks in the current spec and their completion status"

Troubleshooting Ouroboros

ooo command not found after installation

Ensure the Python scripts directory is in your PATH. Run which ouroboros to confirm the binary is installed, then check your shell's PATH. For pipx installations, run pipx ensurepath and restart your terminal.

MCP server not registered in Claude Code after install

Run ouroboros setup (without --runtime) to let it re-detect and register. You can also manually add the server to ~/.claude/claude_desktop_config.json using the JSON config shown above.

Interview hangs or produces vague spec

Be specific in your initial idea — include the target language, key constraints, and what 'done' looks like. If the interview loop is not terminating, run ooo interview --resume to continue from the last checkpoint stored in the ledger.

Frequently Asked Questions about Ouroboros

What is Ouroboros?

Ouroboros is a Model Context Protocol (MCP) server that agent os: stop prompting. start specifying. It connects AI assistants to external tools and data sources through a standardized interface.

How do I install Ouroboros?

Follow the installation instructions on the Ouroboros GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.

Which AI clients work with Ouroboros?

Ouroboros works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.

Is Ouroboros free to use?

Yes, Ouroboros is open source and available under the MIT license. You can use it freely in both personal and commercial projects.

Browse More Coding Agents MCP Servers

Explore all coding agents servers available in the MCPgee directory. Each server includes setup guides for Claude, Cursor, and VS Code.

Quick Config Preview

{ "mcpServers": { "ouroboros": { "command": "npx", "args": ["-y", "ouroboros"] } } }

Add this to your claude_desktop_config.json or .cursor/mcp.json

Read the full setup guide →

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