MCP for wholesale & B2B distribution

Why wholesale benefits from MCP in particular

B2B distribution lives on speed on the phone and by email. A customer asks about availability, a field rep needs the stored price scale, the sales desk has to send out a quote — and the data for all of it is spread across ERP, inventory system and shop. Every answer means switching tools, search screens and lost context.

An MCP server connects your systems to an AI agent through the open Model Context Protocol. Instead of clicking through SAP Business One, weclapp or JTL for every question, your employees ask the agent — and it pulls the answer live from the relevant API. Standardised, without you having to build custom scripts or fragile Zapier chains for every new AI model.

Typical profiles: specialist wholesalers, technical distributors, food and beverage distribution, C-parts and spare-parts trade. Wherever many items, tiered prices and tight delivery dates come together, the integration pays off fastest.

Which systems can be connected

In wholesale, three worlds usually meet. All of them offer dependable interfaces that an MCP server can build on:

• ERP systems: SAP Business One offers the Service Layer (OData/REST), which covers the full business logic from orders to stock movements. weclapp provides a modern REST/JSON API, and Microsoft Dynamics 365 Business Central also has REST-based APIs.
• Inventory management: JTL-Wawi provides a REST API (plus GraphQL from v2.0) for orders, items, customers, invoices and stock — ideal for trading businesses with their own warehouse.
• Shop systems: Shopware and comparable B2B shops have documented admin APIs through which products, stock and orders can be read and written.

For the individual building blocks, see the specific guides: MCP server for SAP Business One, MCP server for weclapp and MCP server for Shopware.

Use cases: what a wholesale MCP server can do in practice

1. Stock & availability in real time “How many pallets of item 4711 are in the North warehouse, and when does replenishment arrive?” The agent reads stock levels, reserved quantities and open purchase orders with suppliers — and gives a reliable availability statement instead of a gut feeling.
2. Prices & customer-specific terms “What net price applies to customer Müller for an order of 500 units?” The agent resolves price lists, discount scales and special terms from the ERP — without the sales desk having to search the terms matrix itself.
3. Order & delivery status “Where is yesterday afternoon’s order?” The agent shows status, tracking and the expected delivery date — and can prepare a status email to the customer as a draft.
4. Suppliers & purchasing Which supplier is the cheapest or fastest for an item? The agent compares stored supplier prices and replenishment lead times and suggests a reorder when stock falls below the minimum level.
5. Quotes & orders as drafts “Create a quote for the items we discussed on the phone.” The agent assembles the quote or order in the ERP, takes over customer address, terms and delivery date — your team reviews once and approves.
6. Cross-system reconciliation Stock from the inventory system against the B2B shop, customer master data between shop and ERP. The agent flags discrepancies — for example when an item appears available in the shop that has long been sold out in the warehouse.

How the integration works

The architecture for wholesale:

AI agent ↔ MCP server (your EU host) ↔ ERP / inventory system / shop (REST, OData or GraphQL)

The concrete steps:

• System inventory: We clarify which systems are the lead systems — usually the ERP for prices and orders, the inventory system for stock, the shop for online orders — and where data ownership lies.
• Tool mapping: We define MCP tools such as check_stock, get_customer_price, get_order_status, list_suppliers, create_quote_draft. Each with a JSON schema, validated inputs and clear error messages.
• Read vs. write: Read queries (stock, price, status) run directly. Write actions (quote, order) are created by the agent as drafts by default — approval by a human, configurable per tool.
• Mapping pricing logic cleanly: Customer-specific prices in particular are delicate. We encapsulate price calculation so that the agent only sees the correct price for the customer in question — no other customers’ terms.
• Logging: Every query and every write action is logged with timestamp, user and diff — important when several people work through the agent.

Data protection, hosting & security

In wholesale, the sensitive data is less personal than business-critical: purchase prices, margins, supplier terms and customer-specific discounts. These must not end up in a foreign US cloud or be mixed between customers. We pay attention to this with every wholesale MCP server:

• EU hosting of the MCP server (e.g. Hetzner or the Azure Germany West Central region), no US edge.
• DPA with the AI provider in EU data residency — Claude via AWS Bedrock (EU region Frankfurt) or Google Vertex AI (EU), alternatively OpenAI Enterprise EU or Azure OpenAI in an EU region.
• Data minimisation per tool: The agent sees only the fields a task needs — no blanket access to the entire terms matrix.
• Role and tenant separation: Field sales, sales desk and purchasing receive different tool permissions.
• Complete audit log, so that every automated action remains traceable.

What does it cost?

Wholesale projects are more demanding than a pure accounting integration, because several systems often work together. Even so, we work here in clear, well-defined steps:

• Start with one use case — usually a stock query or price enquiry first, because that is where the daily benefit is highest. Then expand step by step.
• Clear scope per use case instead of an open-ended hours budget. Scaling in manageable increments.

The exact figure depends on the number of connected systems, the complexity of your pricing-terms logic and the desired tool scope. We give it after a short audit — based on your actual system landscape, not as a flat rate.

Frequently asked questions

Does MCP work with my ERP, such as SAP Business One or weclapp?

Yes. SAP Business One comes with the Service Layer (OData/REST), weclapp with a modern REST API, and JTL-Wawi with a REST API or, from v2.0, a GraphQL API. An MCP server can be built on each of these interfaces, providing exactly the functions you really need as tools.

Can the AI agent see customer-specific prices and terms?

Only as far as you approve it. We encapsulate price calculation so that for each request the agent only ever resolves the correct price for the customer in question — no other customers’ scales, no blanket access to the whole terms matrix.

Can the AI create orders or quotes directly?

Technically yes. In practice, the agent first creates quotes and orders as drafts. Your team approves the final step with price and delivery date — until you have built up enough trust to fully automate individual routines.

How does this stay GDPR-compliant with sensitive supplier and customer data?

MCP server in the EU, DPA with the AI provider in EU data residency, data minimisation per tool and a complete audit log. That way no record leaves the controlled chain — and purchase prices or margins stay where they belong.

What if I run several systems in parallel?

That is exactly the normal case in wholesale. An MCP server can connect ERP, inventory system and shop at the same time and reconcile data between them. More in the guide on the MCP cluster.

Which AI models can be connected?

All MCP-compatible models: Anthropic Claude, OpenAI GPT, Google Gemini, Microsoft Copilot. Switching models later is possible without a new integration.