Odoo Project MCP Server for LangChain 7 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Odoo Project through the Vinkius and LangChain agents can call every tool natively — combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
async with MultiServerMCPClient({
"odoo-project": {
"transport": "streamable_http",
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
}
}) as client:
tools = client.get_tools()
agent = create_react_agent(
ChatOpenAI(model="gpt-4o"),
tools,
)
response = await agent.ainvoke({
"messages": [{
"role": "user",
"content": "Using Odoo Project, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
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.
LangChain's ecosystem of 500+ components combines seamlessly with Odoo Project through native MCP adapters. Connect 7 tools via the Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures — with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
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 LangChain 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 LangChain via MCP
Follow these steps to integrate the Odoo Project MCP Server with LangChain.
Install dependencies
Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save the code and run python agent.py
Explore tools
The agent discovers 7 tools from Odoo Project via MCP
Why Use LangChain with the Odoo Project MCP Server
LangChain provides unique advantages when paired with Odoo Project through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents — combine Odoo Project MCP tools with 500+ LangChain components
Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
Memory and conversation persistence let agents maintain context across Odoo Project queries for multi-turn workflows
Odoo Project + LangChain Use Cases
Practical scenarios where LangChain combined with the Odoo Project MCP Server delivers measurable value.
RAG with live data: combine Odoo Project tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Odoo Project, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Odoo Project tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Odoo Project tool call, measure latency, and optimize your agent's performance
Odoo Project MCP Tools for LangChain (7)
These 7 tools become available when you connect Odoo Project to LangChain 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 LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Odoo Project immediately.
"Search for leads from the website"
"Show recent sales orders"
Troubleshooting Odoo Project MCP Server with LangChain
Common issues when connecting Odoo Project to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersOdoo Project + LangChain FAQ
Common questions about integrating Odoo Project MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.Which LangChain agent types work with MCP?
Can I trace MCP tool calls in LangSmith?
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 LangChain
Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.