Odoo Project MCP Server for Pydantic AI 7 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Odoo Project through the Vinkius and every tool is automatically validated against Pydantic schemas — catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
agent = Agent(
model="openai:gpt-4o",
mcp_servers=[server],
system_prompt=(
"You are an assistant with access to Odoo Project "
"(7 tools)."
),
)
result = await agent.run(
"What tools are available in Odoo Project?"
)
print(result.data)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Odoo Project MCP Server
Connect Odoo ERP to any AI agent — manage your entire business without switching tabs.
Pydantic AI validates every Odoo Project tool response against typed schemas, catching data inconsistencies at build time. Connect 7 tools through the Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code — full type safety, structured output guarantees, and dependency injection for testable agents.
What you can do
- CRM — Search and create leads, track opportunities through your pipeline
- Contacts — Find individual contacts and companies, create new partners
- Sales — List and manage sales orders with full order details
- Notes — Add comments and notes to any record in your Odoo instance
The Odoo Project MCP Server exposes 7 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Odoo Project to Pydantic AI via MCP
Follow these steps to integrate the Odoo Project MCP Server with Pydantic AI.
Install Pydantic AI
Run pip install pydantic-ai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 7 tools from Odoo Project with type-safe schemas
Why Use Pydantic AI with the Odoo Project MCP Server
Pydantic AI provides unique advantages when paired with Odoo Project through the Model Context Protocol.
Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
Model-agnostic architecture — switch between OpenAI, Anthropic, or Gemini without changing your Odoo Project integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Odoo Project connection logic from agent behavior for testable, maintainable code
Odoo Project + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Odoo Project MCP Server delivers measurable value.
Type-safe data pipelines: query Odoo Project with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Odoo Project tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Odoo Project and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Odoo Project responses and write comprehensive agent tests
Odoo Project MCP Tools for Pydantic AI (7)
These 7 tools become available when you connect Odoo Project to Pydantic AI via MCP:
odoo_create_project
project record. The name is the project title. Optionally link it to an existing customer/partner using their res.partner ID. Use when the user wants to set up a new project for internal work, a client engagement, or a product initiative. Create a new project in Odoo, optionally linked to a customer or partner
odoo_create_task
task record in the specified project. Requires the project.project ID (use odoo_list_projects to find it). Optionally assign to a res.users ID and set a deadline in YYYY-MM-DD format. Use when the user wants to add a to-do item, delegate work, or plan project deliverables. Create a new task within an Odoo project, optionally assigning it to a user with a deadline
odoo_list_projects
project records showing all active projects. Returns project name, project manager, linked customer/partner, total task count, start date, and end date. Use when the user asks about ongoing projects, wants a project overview, or needs to find a project ID for task creation. List all projects in Odoo with responsible person, customer, task count, and date range
odoo_list_tasks
task records. Optionally filter by project ID to see tasks for a specific project, or omit to see tasks across all projects. Returns task name, project, assigned users, kanban stage (e.g., New/In Progress/Done), priority (0=normal, 1=important), progress percentage, deadline, and creation date. Use when the user asks about to-do lists, task assignments, project progress, or upcoming deadlines. List project tasks in Odoo with assignee, kanban stage, priority, progress, and deadlines
odoo_list_timesheets
analytic.line records where project_id is set — these are timesheet entries that track hours worked. Returns description, project, task, employee, hours logged (unit_amount), and date. Use when the user asks about time tracking, billable hours, employee workload, or project time allocation. List timesheet entries in Odoo showing employee, project, task, hours logged, and date
odoo_log_timesheet
analytic.line record linking hours to a specific project and task. Requires project.project ID, project.task ID, hours worked, and a description of the work performed. Optionally specify a date (defaults to today). Use when the user wants to log time spent, track billable hours, or record daily work activities. Log a timesheet entry — record hours worked on a specific project task with a description
odoo_update_task
task record. You can change the task name, priority (0=normal, 1=important/starred), deadline (YYYY-MM-DD), or any other writable field. Use when the user wants to rename a task, change its priority, reschedule the deadline, or modify task details. Update an existing task in Odoo — change name, priority, deadline, or other properties
Example Prompts for Odoo Project in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Odoo Project immediately.
"Search for leads from the website"
"Show recent sales orders"
Troubleshooting Odoo Project MCP Server with Pydantic AI
Common issues when connecting Odoo Project to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiOdoo Project + Pydantic AI FAQ
Common questions about integrating Odoo Project MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.Does Pydantic AI validate MCP tool responses?
Can I switch LLM providers without changing MCP code?
Connect Odoo Project with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Odoo Project to Pydantic AI
Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.