Our Method
A proven six-step methodology for building powerful MCP servers and LLM applications for ChatGPT, Gemini, Claude, Copilot, or any other AI assistant
From idea to interaction
Definition
We start by shaping your app's functional scope and user experience within ChatGPT or any LLM-compatible environment supporting MCP servers. Together, we define what your app should do and how it delivers value in a natural, conversational flow.
Connect your data
Data Sources Analysis and Integration
We analyze your data sources and create a tailored plan to connect your internal APIs, databases, documents, or cloud services to your MCP server—ensuring security, performance, and control over sensitive information. Sensitive data remains protected and inaccessible to the LLM, preventing misuse while maintaining the contextual power of your application.
Design the experience
User Interaction Design
We design how users will engage with your system directly inside the LLM—through structured responses or interactive ChatGPT widgets—ensuring clarity, usability, and a smooth conversational experience. We develop and integrate interactive widgets for browsing data or executing small tasks without leaving the LLM environment.
Build the engine
MCP Server Development
Once the definition and design stages are complete, our engineers develop your MCP server along with any web interfaces rendered within the LLM. We use TypeScript for MCP development and React for the interface components. Our development process follows best practices to ensure efficiency, maintainability, and compatibility across your data and AI infrastructure.
Reliable infrastructure
Host and Deploy
We set up the hosting environment, deployment pipelines, authentication mechanisms, scalability considerations, and caching, that keep your application fast, stable, and secure. Whether cloud-based or on-premises, we configure scalable infrastructure, continuous delivery, and monitoring tools to ensure your ChatGPT app runs smoothly at any scale.
Engineered for safety and compliance
Testing and Security Audit
We rigorously test your app's interaction with the LLM to ensure consistent, reliable performance. Because LLM responses are non-deterministic, this testing phase is critical for verifying reliability and preventing hallucinations. Every project concludes with a full security audit to protect your data and users from unauthorized access.
Get in Touch
Ready to start your project? Reach out and let's talk today!