
MCP-Odoo
A bridge that allows AI agents to access and manipulate Odoo ERP data through a standardized Model Context Protocol interface, supporting partner information, accounting data, financial records reconciliation, and invoice queries.
README
MCP-Odoo
Model Context Protocol server for Odoo integration, allowing AI agents to access and manipulate Odoo data through a standardized interface.
Overview
MCP-Odoo provides a bridge between Odoo ERP systems and AI agents using the Model Context Protocol (MCP). This enables AI systems to:
- Access partner information
- View and analyze accounting data including invoices and payments
- Perform reconciliation of financial records
- Query vendor bills and customer invoices
Features
- 🔌 Easy integration with Odoo instances
- 🤖 Standard MCP interface for AI agent compatibility
- 📊 Rich accounting data access
- 🔒 Secure authentication with Odoo
Installation
# Clone the repository
git clone https://github.com/yourtechtribe/model-context-protocol-mcp-odoo.git
cd model-context-protocol-mcp-odoo
# Install dependencies
pip install -r requirements.txt
Configuration
Create a .env
file in the project root with the following variables:
ODOO_URL=https://your-odoo-instance.com
ODOO_DB=your_database
ODOO_USERNAME=your_username
ODOO_PASSWORD=your_password
HOST=0.0.0.0
PORT=8080
Usage
Start the MCP server:
# Using the SSE transport (default)
python -m mcp_odoo_public
# Using stdio for local agent integration
python -m mcp_odoo_public --transport stdio
Documentation
Comprehensive documentation is available in the docs/
directory:
- Documentation Home - Start here for an overview of all documentation
- Implementation Guide - Detailed architecture and implementation details
- Accounting Functionality - In-depth guide to accounting features
- Troubleshooting - Solutions for common issues
- Usage Examples - Practical examples to get started
Development
Project Structure
mcp_odoo_public/
: Main packageodoo/
: Odoo client and related modulesresources/
: MCP resources definitions (tools and schemas)server.py
: MCP server implementationconfig.py
: Configuration managementmcp_instance.py
: FastMCP instance definition
Adding New Resources
Resources define the capabilities exposed to AI agents through MCP. To add a new resource:
- Create a new file in the
resources/
directory - Define your resource using the
@mcp.tool()
decorator - Import your resource in
resources/__init__.py
For detailed instructions, see the Implementation Guide.
License
This project is licensed under the MIT License - see the LICENSE file for details.
Author
Albert Gil López
- Email: albert.gil@yourtechtribe.com
- LinkedIn: https://www.linkedin.com/in/albertgilopez/
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.