Odoo Inventory MCP Server for LangChain 9 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Odoo Inventory 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-inventory": {
"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 Inventory, 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 Inventory 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 Inventory through native MCP adapters. Connect 9 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 Inventory MCP Server exposes 9 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 Inventory to LangChain via MCP
Follow these steps to integrate the Odoo Inventory 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 9 tools from Odoo Inventory via MCP
Why Use LangChain with the Odoo Inventory MCP Server
LangChain provides unique advantages when paired with Odoo Inventory through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents — combine Odoo Inventory 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 Inventory queries for multi-turn workflows
Odoo Inventory + LangChain Use Cases
Practical scenarios where LangChain combined with the Odoo Inventory MCP Server delivers measurable value.
RAG with live data: combine Odoo Inventory tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Odoo Inventory, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Odoo Inventory tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Odoo Inventory tool call, measure latency, and optimize your agent's performance
Odoo Inventory MCP Tools for LangChain (9)
These 9 tools become available when you connect Odoo Inventory to LangChain via MCP:
odoo_get_transfer
picking record with all fields including move line IDs. Use after listing transfers to drill into a specific receipt, delivery, or internal transfer for full details. Get complete details of a specific stock transfer including its individual stock move lines
odoo_list_adjustments
quant records where inventory_quantity_set is true — these are quants with a proposed adjustment that has not yet been applied. Use when the user asks about pending stock corrections, cycle count discrepancies, or inventory adjustments awaiting approval. List pending inventory adjustments that need to be validated or reviewed by a warehouse manager
odoo_list_locations
location records with usage="internal" — the physical locations where stock is stored. Returns location name, full hierarchical path (e.g., WH/Stock/Zone A), and parent warehouse. Use when the user needs to find specific storage locations, plan inventory placement, or understand the warehouse structure. List internal stock locations (bins, zones, shelves) within Odoo warehouses
odoo_list_stock_moves
move records ordered by date descending. Each move represents a single product movement from one location to another. Returns product name, quantity, state, origin/destination locations, and source document. Use when the user needs a granular audit trail of what moved where and when. List recent individual stock movements showing product, quantity, source, destination, and processing state
odoo_list_transfers
picking records — each represents a batch of stock moves like incoming shipments, outgoing deliveries, or internal transfers. Returns transfer reference, partner, operation type, state (draft/waiting/confirmed/assigned/done), source document (e.g., SO or PO number), scheduled date, and source/destination locations. Filter by state to see only pending, ready, or completed transfers. List stock transfers (receipts, deliveries, internal moves) in Odoo with their current processing status
odoo_list_warehouses
warehouse records. Each warehouse has a name, short code (e.g., WH, WH2), and linked partner/address. Warehouses are the top-level organizational unit in Odoo Inventory. Use when the user asks about warehouse locations, needs warehouse codes for transfers, or wants an overview of the logistics network. List all configured warehouses in Odoo with their short codes and addresses
odoo_product_stock
quant records for the given product ID, showing quantity and reserved quantity at each internal location. Use when the user needs to know WHERE stock is located, not just the total — e.g., "how much of Product X is in Warehouse A vs Warehouse B?" Get detailed stock levels for a specific product broken down by warehouse location
odoo_search_inventory_products
product records (variants) by name. Returns product name, internal reference (SKU), quantity on hand (qty_available), forecasted quantity (virtual_available), incoming qty, outgoing qty, category, and product type. Use when the user wants to check stock levels, find products with low inventory, or verify availability before fulfillment. Search products in Odoo Inventory with real-time stock quantities, including available, incoming, and outgoing
odoo_search_lots
lot records by name/number. Returns lot name, associated product, and total quantity in that lot. Use for traceability — when the user needs to find which products belong to a specific batch, or trace a serial number back to its origin. Search for lot numbers or serial numbers in Odoo to trace product batches
Example Prompts for Odoo Inventory in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Odoo Inventory immediately.
"Search for leads from the website"
"Show recent sales orders"
Troubleshooting Odoo Inventory MCP Server with LangChain
Common issues when connecting Odoo Inventory to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersOdoo Inventory + LangChain FAQ
Common questions about integrating Odoo Inventory 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 Inventory 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 Inventory to LangChain
Get your token, paste the configuration, and start using 9 tools in under 2 minutes. No API key management needed.