oduflow 1.15.1

AI-first Odoo development and CI tool with reusable database templates, powered by MCP

Oduflow

An AI-first Odoo development and CI tool, powered by reusable database templates. Oduflow provisions isolated, ephemeral Odoo environments on Docker — one per git branch — and exposes them to AI coding agents via MCP, creating a closed feedback loop that enables fully autonomous Odoo development.

Beyond Vibe Coding: Spec-Driven Development

Vibe coding — chatting with an AI and eyeballing the output — was the first wave. It works for prototypes, but breaks down on real ERP systems where a module must install cleanly, pass tests, and work against production data.

Spec-Driven Development (SDD) is the next step: you write a precise specification of what the module should do, and the AI agent autonomously implements how — because it has a closed feedback loop with the running system:

┌─────────────────────────────────────────────────────┐
│                    AI Agent                          │
│          (Cursor, Cline, Amp, Claude, …)             │
└──────┬──────────────────────────────▲────────────────┘
       │ 1. Read spec                 │ 5. Read errors,
       │ 2. Write code                │    fix code,
       │ 3. Install module via MCP    │    retry
       │ 4. Click-test UI via         │
       │    Playwright MCP            │
┌──────▼──────────────────────────────┴────────────────┐
│               Oduflow (MCP Server)                    │
│  • install_odoo_modules → traceback or success        │
│  • run_odoo_tests → test pass/fail with details       │
│  • get_environment_logs → runtime errors              │
│  • upgrade_odoo_modules → upgrade output              │
├──────────────────────────────────────────────────────┤
│            + Playwright MCP / other tools              │
│  • Navigate Odoo UI, click buttons, fill forms        │
│  • Verify business logic end-to-end                   │
│  • Validate acceptance criteria from the spec         │
└──────────────────────────────────────────────────────┘

The agent writes code, installs the module, reads the traceback, fixes the error, retries — and when it installs cleanly, it can open the browser via Playwright MCP to click through the UI, verify business flows, and validate acceptance criteria — all without human intervention.

	Vibe Coding	Spec-Driven Development
Input	Conversational prompts	Formal specification with acceptance criteria
Feedback	Human eyeballs the code	System returns errors, test results, and UI state automatically
Iteration	Human copy-pastes errors back	Agent retries autonomously via MCP
Scope	Single files, prototypes	Full modules against real databases
Verification	"Looks right"	Module installs, tests pass, UI works on production data

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Quick Start

1. Install

pip install oduflow

2. Configure

cp .env.example .env
# Edit .env — at minimum set paths and optionally ODUFLOW_AUTH_TOKEN

3. Initialize the system

oduflow init

4. Start the MCP server

oduflow

The server starts on http://0.0.0.0:8000 by default.

5. Connect an MCP client

Point your MCP client (Cursor, Cline, Amp, etc.) to http://<host>:8000/mcp.

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Documentation

For full documentation, visit oduflow.dev or see the docs/ folder:

• Installation & Configuration
• Use Cases & Workflows
• Template Management
• Environment Management
• Auxiliary Services
• Extra Addons Repositories
• Web Dashboard & REST API
• MCP Tools Reference
• CLI Reference
• Traefik Routing (Auto-HTTPS)
• Multi-Instance Support
• Authentication & Security
• Running in Docker
• Internals
• Licensing

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Licensing

Oduflow is source-available under the Polyform Noncommercial License 1.0.0. Commercial use requires a license — visit oduflow.dev.