About Us

The technical partner enterprises trust to build MCP applications that work in production, beyond the demos.

Who We Are

MCP Apps Builders is a technical partner building production-grade AI applications using the Model Context Protocol (MCP) and the ChatGPT Apps SDK.

We help enterprises navigate a fundamental shift: ChatGPT is becoming a distribution channel, not just a tool.

We’re not a traditional agency that added AI to an existing portfolio.
We advise and build. We write production code for AI systems that operate under real-world constraints.

Our Mission

We build AI systems that work in production.

We train AI practitioners and software engineers to build and maintain MCP applications with production realities in mind.

We support teams through strategic consulting around MCP applications—helping them understand trade-offs, constraints, and when to build versus when to pause and strengthen foundational systems.

What Makes Us Different

Builder-first approach

We build what we advise. Every recommendation is grounded in hands-on production experience, not slide decks.

Business outcomes over technical novelty

We prioritize results that matter: systems that ship, users who adopt, and problems that get solved.

Multi-platform expertise

ChatGPT today, Gemini today, and whatever comes next. Our code is auditable, and our systems are portable by design.

Holistic vertical approach

We cover the full lifecycle: strategic consulting, app building, and system design—all under one roof.

No vendor lock-in

Our code is auditable and open when possible. You own what we build.

What We Refuse to Be

  • AI hype merchants — we don’t promise transformation, we deliver working systems
  • Generic consultants who advise but don’t build — we write production code
  • Proof of Concept factories — we build Proof of Value with measurable outcomes
  • Vendor lock-in architects — our systems are portable, and our choices are explicit

Our Expertise

MCP & ChatGPT Apps (Production Systems)

  • MCP server architecture and development
  • Conversational UI component design
  • Tool and template implementation
  • Widget runtime and state management
  • OAuth authentication flows
  • Production deployment and observability

Technical stack mastery

  • MCP Servers: Tools, templates, widget runtime
  • Conversational UI: Native ChatGPT interface components
  • State Management: Persistent data across conversations
  • Authentication: User identity and OAuth
  • Observability: Monitoring, tracing, and error handling

Production readiness

  • Latency requirements and optimization
  • Error handling and graceful degradation
  • Security and privacy considerations
  • Real-world constraint analysis

Evaluation & reliability

  • Task-level and system-level evaluation
  • Tool-call accuracy and failure analysis
  • Guardrails, fallbacks, and reliability metrics
  • Evidence-based go / no-go decisions

Our Values

Pragmatism over hype

We discuss trade-offs, admit uncertainty, and are explicit about what MCP apps can—and cannot—do.

Fast go-to-market for a strategic exploration

Speed matters, but not at the cost of building the wrong thing. We balance velocity with validation.

Clarity over complexity

We use precise language: systems, production, constraints—not magic, revolution, or plug-and-play.

Long-term thinking

We design for sustainability. Your systems should work months from now, not just during the demo.

Craft, execution & excellence

High standards, quality code, and systems that ship. We care deeply about how things are built.

Trust & responsibility

We’re honest about limits and risks. If something shouldn’t be built, we’ll explain why.

The Team

Our team includes experienced software engineers, AI specialists, and technical strategists with hands-on experience building AI systems in production environments.

We’ve built applications serving thousands of users. We’ve also learned where systems break—and we bring those lessons into every engagement.

We train development teams on MCP best practices and advise organizations on AI strategy with a focus on real-world outcomes.

Our Approach

1. Understand & Assess

Every engagement starts by understanding your goals, constraints, and risks. We map trade-offs before writing code.

2. Decide with Production in Mind

We design architectures that account for latency, error handling, security, user behavior, and scale.

3. Build & Validate

We develop with speed and rigor, but every feature must survive contact with production.

4. Deploy & Operate

We deploy with observability in place—because shipping is only the beginning.

5. Transfer & Empower

We ensure your team understands what was built and can maintain it with full confidence.

Let’s Connect

Interested in working together?
Start a conversation and let’s talk about what AI can realistically, and responsibly, do for your business.