Our services for agent-ready ecosystems
MCP server development
Model Context Protocol servers make your systems directly accessible to AI agents via standardised interfaces. MCP provides secure, structured communication between agents and your platforms, enabling complex multi-step workflows.
CLI integration for agents
We develop command-line interfaces that give AI agents direct, reliable access to your systems. CLI integration provides higher reliability and lower operational costs for integration points where agents need system-level access.
llms.txt implementation
Structured, human-curated entry points help AI agents understand your content and services. llms.txt ensures your digital ecosystem is discoverable and comprehensible to language models and AI agents.
Computer use-ready design
We assess and optimise your interfaces for AI agents that navigate visually, just as humans do. These agents click, scroll, read, and fill forms — we ensure your platform supports these interactions reliably.
Agent-ready ecosystem design
We evaluate your digital architecture for agent readability and implement targeted adjustments. Our approach creates ecosystems that are usable for both human users and AI agents, regardless of how they access your services.
Structured data for AI agents
Your existing content, product data, and platform information is translated into machine-readable formats that agents can directly understand and use, reducing the need for human interpretation.
WebMCP integration
WebMCP brings Model Context Protocol functionality to browsers, making your web platform directly accessible to AI agents via open standards and preparing for next-generation AI agent-driven traffic.
Multi-step agentic workflows
We design and implement complex workflows that enable AI agents to perform multi-step processes across your systems, from information gathering to transaction completion, while maintaining security, governance and compliance.
Let's discuss your agent readiness needs
Our approach to agent-ready ecosystems
The customer journey used to mean humans navigating your website. Increasingly, it means AI agents arriving on behalf of humans via MCP, CLI interfaces, llms.txt, or by visually navigating your interface through computer use. We focus on making your existing digital environment structurally accessible to external agents.
From informational to actionable
Traditional digital platforms provide information to people. Agent-ready platforms enable AI agents to take action: initiate payments, request data, start processes. This difference lies in architecture, not business intent. We design this distinction deliberately, creating infrastructure that supports both information access and action execution.
Discoverable for every agent, at every layer
Agent readability starts with structured data but extends through architecture levels. llms.txt ensures language models understand your content via structured entry points. WebMCP makes web platforms usable for browser-level agents. MCP servers provide standard interfaces for deeper systems, and CLI integrations offer direct, reliable paths for agents requiring system access.
Proven in practice, scalable to production
Open protocols form the foundation of sustainable agent-ready systems. MCP is an open standard that delivers proven results. Brussels Airport, Worldline, and Feyenoord have successfully implemented agent-ready infrastructure using this approach. The progression from proof of concept to production requires careful guidance, with observability and quality assurance integrated from the beginning to ensure reliable scaling.
Why work with us?
MCP expertise built in production
We've implemented MCP for Worldline (live, January 2026), Brussels Airport (proof of concept), and Feyenoord (DXP integration). This hands-on experience provides practical insights for production deployments. The difference between 'AI-ready' and 'agent-ready' is fundamental: we build the infrastructure layer that makes external agent interaction possible.
Right integration path for each ecosystem challenge
MCP and CLI are complementary approaches. MCP suits structured API communication, multi-tenant security, and enterprise OAuth requirements. CLI provides direct system access, higher reliability, and lower costs for specific integration points. We select the optimal approach for your ecosystem, team, and objectives.
Existing ecosystem enhancement
Making your ecosystem agent-ready doesn't require complete rebuilding. We assess your current digital environment (CMS, APIs, data structures, CLI interfaces) and determine targeted adjustments that open platforms to AI agents, delivering quick results without unnecessary disruption.
Technology-agnostic and standards-driven approach
We use MCP because it's an open standard, not a proprietary solution. We choose protocols that fit your stack and scale requirements, avoiding vendor lock-in and closed ecosystems that create supplier dependency.
Architecture to business case alignment
An agent-ready ecosystem involves both technical implementation and strategic positioning. We help build internal business cases, demonstrating value delivery, customer journey improvements, and leadership positioning, ensuring technology and business goals align.
