Most teams that run Odoo already have the data they need locked inside the ORM — sales orders, stock moves, invoices, project tasks, CRM leads — but getting an answer still means clicking through menus, building a filtered list view, or exporting to a spreadsheet. The moment you want an AI assistant to help ("what changed on this customer's overdue invoices this week, and draft a follow-up"), Odoo native runs out of road: there is no supported bridge that lets a modern AI client read live records, respect a given user's ir.model.access.csv and record rules, and act on the result without someone hand-writing XML-RPC glue for every request. Bolting a raw API key onto a chatbot is worse — it ignores multi-company boundaries, leaks fields the user should never see, and hands an unpredictable model unbounded write access to production.

The Advanced MCP Server is a made-to-order Odoo integration that ECOSIRE builds, installs, and supports for you. It implements the Model Context Protocol as a thin, security-first server that sits in front of your Odoo instance and speaks to AI assistants as a set of well-defined tools: query records, read a specific document, run a saved report, or invoke a whitelisted automated action. Under the hood each session authenticates as a real Odoo user and calls the ORM through the XML-RPC/JSON-RPC API — so every read and write is filtered by that user's groups, ir.model.access.csv grants, and record rules exactly as if they were logged into the web client. There is no god-mode key: if a sales rep can't see another team's pipeline in Odoo, the assistant can't either.

Technically, we ship the MCP layer plus a companion Odoo module (a proper __manifest__.py, models/ extending models.Model, and security definitions) that declares the tool surface: which models are queryable, which fields are exposed or masked, which QWeb reports and ir.actions.server automated actions the assistant may trigger, and hard guardrails on writes (allow-listed models/fields, per-tool rate limits, and confirmation gates on anything financial). Query tools translate a natural-language ask into a validated search_read with domain, field projection, and pagination — never raw SQL — while report tools stream the same PDFs/spreadsheets your users already trust. Every call is logged to an audit trail (user, tool, arguments, affected records) so you can see precisely what the AI did. It runs against Community or Enterprise and is built and tested for Odoo 17.0, 18.0, and 19.0; Enterprise-only surfaces (for example studio-built models or accounting features) are wired only when your edition actually has them.

Delivery is build-to-order. After a short scoping call we confirm the exact models, reports, and actions to expose, agree the security matrix, then build against a copy of your database, hand you the module and MCP server on a staging environment for UAT, and go live only once you sign off — typically one working week from confirmed scope. You receive the full source, a git repo handover, and a support window. Pricing starts from $999 (indicative, single-company base scope); broader tool surfaces, multi-company record-rule design, additional AI-client integrations, and extra automated-action workflows increase the quoted scope.