Accelerate your current retail AI agent initiatives
Put AI agents into production without breaking trust or complicating operations
What retail organizations need before deploying AI agents
Stacklok’s Model Context Protocol (MCP) Platform ensures agents are never over-privileged, poorly governed or too fragile to scale. We help retailers move from pilot to production.
Controlled access
Limit AI agent access to only the specific tools, APIs, and datasets required for a task, protecting customer data, pricing systems, and inventory from unintended actions.
Full visibility
Integrate with your existing observability stack (Datadog, Splunk, and more) to monitor how AI agents interact with systems in real time. Every action is logged, traceable, and measurable.
Simple integration
Give developers, analysts, and operators a single, consistent endpoint to approved tools. Eliminate one-off integrations and reduce friction as AI use expands across teams.
Apply MCP to high-impact retailer use cases
Accelerate your existing AI initiatives and integrate with your current AI stack
Developer productivity
Embed internal data into developer workflows without over-privileging AI systems. Connect IDEs like Cursor or Claude Code to your identity provider (Okta, Entra, etc.) and observability solution
Fraud detection
Connect AI agents to multiple internal systems to detect account abuse, return fraud, and payment anomalies without exposing sensitive infrastructure.
Pricing optimization
Enable AI agents to analyze sales, inventory, and demand signals while strictly controlling access to pricing engines and promotional systems.
The State of MCP in Retail 2026
We surveyed 100 technical leaders at leading retailers to explore their Model Context Protocol progress and priorities. Find out where you stand relative to your peers. Full study results are available with no forms to fill out.
Why retail leaders choose Stacklok
Leaders trust our MCP platform because we:
Run in your VPC
Stacklok runs inside your Virtual Private Cloud, keeping customer data, transaction flows, and operational logic within your control, not routed through third-party SaaS services.
Built on open source
Stacklok builds in the open, with the community. Our popular ToolHive platform can solve many of your MCP challenges immediately, and ensures a sustainable path forward
Offer a full platform
Start by curating your own MCP registry or implementing a custom MCP gateway, and then expand to the complete Stacklok MCP platform according to your timeline and need
Take the next steps
Continue with your due diligence and know that we’re always available for an open conversation
for Enterprise
Start by curating a registry of trusted MCP servers for your enterprise
for Individuals
Dive into the ToolHive repo and docs, and then engage directly with our team.
Frequently asked questions
Stacklok’s Enterprise Model Context Protocol Platform is designed for fast-paced industries like retail.
Stacklok’s Model Context Protocol Platform helps retailers securely control how AI models access tools, data, and workflows. It provides a standardized, auditable way to define what context an AI system is allowed to use, under what conditions, and with what safeguards. This allows retailers to deploy AI safely without exposing sensitive systems or data.
Retailers rely on many interconnected systems that directly impact customers, from product availability to order fulfillment. When AI systems interact with these systems, mistakes can lead to pricing errors, inventory issues, or poor customer experiences. Model Context Protocol ensures AI systems only access what they are allowed to, helping retailers use AI responsibly and reliably.
Many AI tools focus on generating recommendations or insights. Stacklok focuses on controlling how AI systems interact with real retail systems. It provides a safety layer that sits underneath AI-powered applications, ensuring they operate within defined boundaries rather than acting freely.
Yes. Stacklok helps retailers limit the blast radius of AI-driven automation by enforcing explicit access and action rules. This reduces the risk of unintended changes to pricing, inventory, or customer records. Retail teams can confidently automate processes knowing guardrails are in place.
Yes. Stacklok is designed to work alongside existing AI models, commerce platforms, and internal systems. It does not require replacing current tools. Instead, it provides a consistent way to manage AI access across the retail technology stack.