Great discussion topic! Here is a breakdown of the three MCP setups with pros and cons for each:

1. Running MCP Server Locally (Laptop)
2. Best for: Development, testing, personal use.
3. Pros: Easy to set up, no server costs, full control, great for experimenting.
4. Cons: Only works when your laptop is on and connected. Not suitable for production or team use.
5. How: You run the MCP server as a local process (Node.js or Python), connect it to your Odoo instance via the JSON-RPC API or XML-RPC, and configure your AI client (Claude Desktop, Cursor, etc.) to point to localhost.

2. Run MCP as an Odoo Module

Best for: Tight integration with Odoo, single-server deployments.

Pros: Everything lives in one place, can access Odoo internals directly without going through the external API, simpler deployment.

Cons: Couples your MCP to your Odoo version, upgrades can break it, may add load to your Odoo server.

Note: Odoo 19 introduced a native MCP endpoint. If you are on Odoo 19+ (Enterprise), check the built-in AI/MCP feature in Settings first before building a custom module.

3. Hosted MCP Server (Separate Infrastructure)

Best for: Production environments, team use, multi-user setups.

Pros: Always available, scalable, decoupled from Odoo upgrades, can serve multiple AI clients.

Cons: Adds infrastructure complexity and cost. You need to manage authentication and keep the Odoo API credentials secure.

How: Deploy on a VPS, Docker container, or a serverless function. Connect to Odoo via JSON-RPC. Use an API key or OAuth for authentication.

General Recommendation:

For getting started quickly: local setup.

For a production team environment: hosted separate server.

For Odoo 19+ Enterprise users: try the built-in MCP/AI integration in Odoo Settings before building anything custom.

Happy to share more details on any specific setup approach!