How do I get a Nabis Access Token?

Log in to the Nabis Platform, navigate to the Developer settings, and generate a new V2 Access Token.

Which markets are supported?

The API supports all active Nabis markets, including California and New York.

Nabis MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: Nabis
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Nabis through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

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 Nabis "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Nabis?"
    )
    print(result.data)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Nabis MCP Server

Connect your Nabis account to empower your AI agents with wholesale and distribution capabilities. This server interfaces with the Nabis Platform V2 API for real-time visibility into the cannabis supply chain.

Pydantic AI validates every Nabis tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through 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

Order Management — List and inspect wholesale orders across markets like CA and NY
Inventory Visibility — Track stock levels across different warehouses in real-time
Retailer Insights — Access detailed information about retailers and their license status
Financial Monitoring — Track invoices, aging reports, and payment statuses
Logistics Coordination — Stay updated on warehouse locations and delivery schedules

The Nabis MCP Server exposes 10 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 Nabis to Pydantic AI via MCP

Follow these steps to integrate the Nabis 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 10 tools from Nabis with type-safe schemas

Why Use Pydantic AI with the Nabis MCP Server

Pydantic AI provides unique advantages when paired with Nabis 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 Nabis integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Nabis connection logic from agent behavior for testable, maintainable code

Nabis + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Nabis MCP Server delivers measurable value.

Type-safe data pipelines: query Nabis with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Nabis tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Nabis and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Nabis responses and write comprehensive agent tests

Nabis MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Nabis to Pydantic AI via MCP:

get_days_off

Get Nabis days off

get_invoice

Get invoice details

get_order

Get details for a specific order

get_retailer

Get retailer details

get_warehouse_count

Get warehouse stock counts

list_inventory

List inventory quantities

list_invoices

List invoices

list_orders

List Nabis wholesale orders

list_retailers

List retailers

list_warehouses

List warehouses

Example Prompts for Nabis in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Nabis immediately.

"List all pending Nabis orders."

"What is the stock level for product 'Blue Dream' in the LA warehouse?"

Troubleshooting Nabis MCP Server with Pydantic AI

Common issues when connecting Nabis to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Nabis + Pydantic AI FAQ

Common questions about integrating Nabis MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an 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?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Nabis MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.