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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:

  • CRM Management: Complete lead/opportunity lifecycle management with Universidad ISEP customizations

  • Partner Management: Comprehensive contact and customer/supplier management

  • Accounting Analysis: View and analyze financial data including invoices and payments

  • Academic Programs: University-specific program tracking and enrollment management

  • Data Integration: Support for Mautic CRM and Google Analytics integration

  • Multi-team Support: Sales team and workflow management

Related MCP server: MCP-Odoo

Features

  • ๐Ÿ”Œ Easy integration with Odoo instances

  • ๐Ÿค– Standard MCP interface for AI agent compatibility

  • ๐Ÿ“Š Rich accounting and CRM data access

  • ๐ŸŽ“ University-specific academic program management (ISEP)

  • ๐Ÿ‘ฅ Complete partner/contact lifecycle management

  • ๐Ÿ“ˆ CRM analytics and dashboard statistics

  • ๐Ÿ”„ Lead to opportunity conversion workflows

  • ๐Ÿข Multi-team sales management

  • ๐Ÿ”’ 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:

Available Tools

CRM Management

  • list_leads - List and filter leads/opportunities with Universidad ISEP custom fields

  • get_lead_details - Get comprehensive lead information

  • create_lead - Create new leads with academic program tracking

  • update_lead - Update lead information and progress

  • convert_lead_to_opportunity - Convert leads to opportunities

  • get_crm_dashboard_stats - Get performance metrics and analytics

Partner Management

  • list_partners - List and filter contacts/companies

  • get_partner_details - Get detailed partner information

  • create_partner - Create new partners/contacts

  • update_partner - Update partner information

Academic Programs (ISEP Specific)

  • get_academic_programs - List available academic programs

  • list_crm_stages - Get CRM workflow stages

  • list_crm_teams - Get sales teams

  • get_lead_activities - Get lead-related activities

Accounting (Existing)

  • list_vendor_bills - List supplier invoices

  • list_customer_invoices - List customer invoices

  • list_payments - List payments with filtering

  • reconcile_invoices_and_payments - Generate reconciliation reports

Development

Project Structure

  • mcp_odoo_public/: Main package

    • odoo/: Odoo client and related modules

    • resources/: MCP resources definitions (tools and schemas)

    • server.py: MCP server implementation

    • config.py: Configuration management

    • mcp_instance.py: FastMCP instance definition

Adding New Resources

Resources define the capabilities exposed to AI agents through MCP. To add a new resource:

  1. Create a new file in the resources/ directory

  2. Define your resource using the @mcp.tool() decorator

  3. 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 Lรณpez

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

No tool schema history has been recorded yet.

Maintenance

ActivityInactive
ResponsivenessNo issues

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Related MCP Connectors

  • Odoo ERP for AI agents: hosted OAuth endpoint, gated writes, one endpoint for every instance.

  • MCP server unifying ERPs, CRMs, APIs and knowledge base for Claude, ChatGPT and Gemini.

  • The Mercado Pago MCP Server implements the Model Context Protocol to provide AI agents and LLMs with access to Mercado Pago's APIs and tools within compatible development environments. It acts as an intermediary that translates Mercado Pago resources into executable functions (tools) that AI applications can invoke to perform actions and automate flows. The server simplifies integration, enables using documentation to implement or improve code, and optimizes operations through natural language interactions without manual implementations.

  • Model Context Protocol server for the Apideck Unified API. Connect any MCP-compatible agent framework to 100+ accounting systems, HRIS platforms, file storage providers, and more through one integration. More information https://www.apideck.com/mcp-server

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