No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by ivnvxd · MCP Server · ★ 397
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is mcp-server-odoo safe to install? View the security audit →
MCP Server for Odoo An MCP server that enables AI assistants like Claude to interact with Odoo ERP systems. Access business data, search records, create new entries, update existing data, and manage your Odoo instance through natural language. Works with any Odoo instance! Use YOLO mode for quick testing and demos with any standard Odoo installation. For enterprise security, access controls, and production use, install the Odoo MCP module. Features 🔍 Search and retrieve any Odoo record (customers, products, invoices, etc.) ✨ Create new records with field validation and permi
| Stars | 397 |
| Forks | 186 |
| Language | Python |
| Category | MCP Server |
| License | MPL-2.0 |
| Quality Score | 75.6381509902148/100 |
| Open Issues | 8 |
| Last Updated | 2026-10-02 |
| Created | 2025-03-22 |
| Platforms | mcp, python |
| Est. Tokens | ~19k |
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mcp-server-odoo is Model Context Protocol (MCP) server that enables AI assistants to securely interact with Odoo ERP systems through standardized resources and tools for data retrieval and manipulation.. It is categorized as a MCP Server with 397 GitHub stars.
mcp-server-odoo is primarily written in Python. It covers topics such as ai, erp, llm.
You can find installation instructions and usage details in the mcp-server-odoo GitHub repository at github.com/ivnvxd/mcp-server-odoo. The project has 397 stars and 186 forks, indicating an active community.
mcp-server-odoo is released under the MPL-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to mcp-server-odoo on Agent Skills Hub include jadx-mcp-server, odoo-mcp-pro, mcphub.nvim. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: