Do you remember when your phone couldn’t talk to your headphones? It was a mess of cables, adapters, and the question: “Is this the right connector?” Then Bluetooth came along – and suddenly everything just worked together.
We’re in the middle of a similar technological shift again. But this time it’s not about audio – it’s about artificial intelligence (AI). Powerful AI applications like ChatGPT, Claude, or industry-specific AI models are already on the market. But they often operate in isolation – side by side, without any real connection to your company data. Like a top-tier smartphone that isn’t connected to anything.
The solution is called the Model Context Protocol – MCP for short. And the MCP Server is the core of this new AI infrastructure.
What is the Model Context Protocol (MCP)? – The Open Standard for AI Integration
The Model Context Protocol (MCP) is an open-source standard developed by Anthropic in November 2024. Its goal: to create a universal “language” that allows AI applications to securely and consistently communicate with external systems, data sources, and tools – without requiring complex, custom API integrations for each individual connection.
Before MCP, teams had to build separate connections for every tool combination. The result: duplicated effort, inconsistent security, and systems that were hard to maintain. MCP solves this so-called M×N integration problem through a single standardized protocol layer – similar to Bluetooth for audio devices or USB-C for hardware connections.
Since its introduction, MCP has seen remarkable adoption: OpenAI, Google DeepMind, and Microsoft have integrated the protocol into their products. In May 2025, Microsoft even announced native MCP integration in Windows. Today, more than 2,000 platforms worldwide already use an MCP interface.
MCP Server and MCP Clients: How the Architecture Works
The MCP ecosystem is based on a clear client-server architecture with three central components:
MCP Host (the AI application)
The host is the AI application itself – such as Claude, ChatGPT, or a custom enterprise AI agent. It receives user requests and coordinates which servers should be contacted. A host can query multiple MCP servers simultaneously.
MCP Clients: The bridge between AI and data
MCP clients are embedded within AI applications. They discover available MCP servers, establish connections, and call tools and resources. MCP clients use the standardized JSON-RPC 2.0 protocol, making them compatible with any compliant MCP server – regardless of vendor.
MCP Server: The heart of AI integration
The MCP server is the key link. It is a lightweight program that translates external systems – databases, CRM, ERP, PIM, DAM, calendars, GitHub, and more – into a standardized format that AI models can directly understand and use.
An MCP server provides three core functions:
- Tools: Executable actions the AI agent can perform on request (e.g., writing product data, creating tickets, generating documents)
- Resources: Structured data sources provided contextually to the AI (e.g., product catalogs, customer data, real-time system information)
- Prompts: Predefined templates that guide AI agents for specific tasks
The MCP server enables decoupling: the AI application doesn’t need to know how GitHub’s API works – the MCP server handles that complexity. This not only improves security but makes AI integrations truly scalable for the first time.
What an MCP Server Enables: From Reactive Tool to Active AI Agent
Using MCP servers fundamentally changes how AI operates in organizations. AI systems no longer just respond to questions – they can take action.
An MCP server enables:
- Real-time access to up-to-date information: Instead of relying on outdated training data, AI retrieves live data directly from your systems – CRM, ERP, product databases, or calendars.
- Multi-step AI agent workflows: An AI agent can fetch data from one source, interpret it, generate a document, and automatically store it in a company system – all in a single flow.
- Full data control and security: Companies define exactly which data and functions are accessible to the AI model. Existing authentication systems like OAuth or API keys are seamlessly integrated.
- Platform independence: MCP servers provide SDKs for Python, TypeScript, Java, and C# – and work across different AI models and cloud environments.
- Reusability: Once set up, an MCP integration can be reused for countless new use cases – without rebuilding it each time.
MCP Server in PIM Systems: AI Applications That Truly Understand Your Product Data
Let’s turn to something close to Viamedici’s heart: Product Information Management (PIM). This is where an integrated MCP server fully unleashes its potential – transforming isolated product data into connected, intelligent knowledge.
With an MCP server in your PIM system, AI doesn’t just generate simple text suggestions – it understands your entire product landscape. It has access to up-to-date information about structures, relationships, and quality standards – in real time, in context, without manual effort.
AI agents with MCP in PIM can:
- Instantly understand product structures and relationships – even with thousands of SKUs
- Automatically detect gaps and errors in product data and suggest corrections
- Improve categorizations and content – multilingual and channel-specific
- Automatically adapt data for webshops, marketplaces, Amazon, ERP, and print
- Tag assets with metadata and prepare them for publication
- Generate sustainability and compliance reports using live data
- Enrich configurators with suitable add-on offers (CPQ)
All in real time. All in context. No more data silos, no more switching between systems.
From AI Islands to AI Ecosystems: Why the MCP Server Makes the Difference
Many companies already use multiple AI models and tools – but they operate side by side, not together. The result: AI islands – powerful standalone solutions without a connecting infrastructure.
The MCP server builds the crucial bridge. It enables AI not only to respond to questions but to understand, support, and extend processes. The AI becomes aware of your meetings, product data, customer information, and workflows – and evolves into a true strategic partner.
This is the core of AI transformation: no longer isolated AI applications, but a connected AI ecosystem – built on an open, secure, and scalable standard.
How Could an AI-Powered PIM Ecosystem Change Your Strategy?
Ask yourself these questions:
- What would improve if your data quality were continuously validated by AI in real time?
- What if assets were automatically tagged, categorized, and published?
- Could your configurator automatically suggest relevant add-ons – personalized and in real time?
- Would your sustainability reporting become more reliable and efficient with live system data?
- How many hours could your team save if AI agents automatically prepared product data for each channel?
Viamedici EPIM/5 with MCP Server: The AI-Powered PIM Ecosystem
At Viamedici, we have a clear goal: to transform product information into connected, intelligent knowledge. EPIM/5 with an integrated MCP server is our answer to a future where AI doesn’t just assist – but understands, collaborates, and enhances.
Our modules at a glance:
- VIA/MDM: Centrally manage master data for products, customers, and suppliers – clean, consistent, reliable. The foundation for any AI application working with up-to-date information.
- VIA/PIM360°: Manage product data, maintain multilingual content, and distribute it across all channels – webshops, marketplaces, Amazon, ERP, print. With MCP integration, AI agents analyze your data quality in real time.
- VIA/DAM: Manage media like images, videos, and logos intelligently – with AI-driven metadata tagging, smart search, and direct integration with CMS and marketing tools.
- VIA/Configuration (CPQ): Smart configuration with guided selling, ease of use, multilingual support, and B2B/B2C integration. AI agents can automatically suggest add-ons.
Book a Demo Now and Experience the Future of Your Product Data
If you’re ready to move from AI islands to a truly AI-powered PIM ecosystem, talk to us. Discover Viamedici EPIM/5, request a demo, or get expert advice on MCP server and AI agent integration.
About the Author
Boris Jusseit is an Enterprise Solution Architect at Viamedici. He helps companies solve complex PIM challenges through well-designed strategies, AI adoption, and digital processes – with a strong focus on efficiency, data quality, and user experience.
