Make your internal systems AI-accessible
We design and ship Model Context Protocol servers so any compatible AI (Claude, GPT, your own agents) can securely call your APIs, databases, and tools.
What is MCP — and why does it matter?
The Model Context Protocol is an open standard that lets AI models interact with external tools and data sources. Think of it as a universal adapter between AI and your systems.
Instead of building custom integrations for every AI model, you build one MCP server. Any MCP-compatible AI can then securely access your internal APIs, databases, and tools.
Building one well is the hard part — schema design, authentication, security, performance, and observability all matter.
MCP is a new protocol — limited documentation and examples.
Designing tool schemas requires deep understanding of AI capabilities.
Security is critical — AI will have access to internal systems.
Error handling must be robust for autonomous AI usage.
Performance matters — agents make many tool calls per task.
Tool composability reshapes how you design internal APIs.
What we build
Production-ready MCP servers that give AI models controlled access to your systems.
API-to-MCP bridges
We wrap your existing REST, GraphQL, or gRPC APIs as MCP tools — with proper input validation and error handling.
Custom MCP servers
Purpose-built servers for database queries, file management, workflow automation, or any internal capability you want AI to access.
Auth & authorisation
Fine-grained access control for every tool — API keys, OAuth, and role-based permissions.
Security guardrails
Input validation, rate limiting, audit logging, and sandboxing protect your systems from autonomous AI usage.
Monitoring & debugging
Full visibility into how AI models use your tools. Track usage, debug failures, optimise performance.
Performance optimisation
Caching, connection pooling, and async processing — built for AI workloads that make hundreds of tool calls.
Every engagement includes
- Custom MCP server development.
- API-to-MCP bridge implementation.
- Authentication and access control.
- Security guardrails and rate limiting.
- Tool schema design and optimisation.
- Monitoring and debugging dashboard.
- Performance testing and optimisation.
- Documentation and team training.
Ready to make your APIs AI-accessible?
Let's discuss how MCP can connect your internal systems to the world of AI.