• 4 min read

MCP Apps Extension: Interactive AI Interfaces Come to Life

MCP Apps Extension: Interactive AI Interfaces Come to Life

Trend Overview

The Model Context Protocol just got visual: AI assistants can now deliver interactive user interfaces, not just text responses.

What's Happening:

Anthropic, OpenAI, and the MCP community have jointly introduced the MCP Apps Extension (SEP-1865) — a standardized way for AI assistants to deliver interactive user interfaces within conversational experiences.

  • What it is: An extension to the Model Context Protocol that allows MCP servers to deliver rich, interactive UIs (charts, forms, dashboards) instead of just text
  • Who's behind it: Collaboration between Anthropic, OpenAI, and the MCP-UI community (led by Ido Salomon and Liad Yosef)
  • Why now: MCP has been limited to text exchanges, creating friction for visual data and complex inputs. The community demanded a standardized solution to prevent ecosystem fragmentation
  • Key capabilities: Pre-declared UI templates, bidirectional communication via JSON-RPC, security-first sandboxed iframes, and backward compatibility

Example: Instead of an AI returning raw JSON data for a sales chart that you'd need to interpret, it can now display an interactive bar chart directly in your chat interface — complete with hover effects, filtering, and drill-downs.

Why It Matters

The Big Picture

This isn't just a technical update — it's a fundamental shift in how AI tools can integrate into business workflows. For OC companies already exploring AI assistants, this means your custom tools can now deliver dashboards, configuration panels, and data visualizations directly within conversational interfaces like Claude or ChatGPT. No more awkward back-and-forth trying to describe visual information through text.

Who's Most Affected

Immediate impact:

  • Software teams building internal AI tools can now deliver richer experiences without building separate UIs
  • Data analysts and BI teams can present interactive visualizations through conversational interfaces
  • Operations teams using AI for complex workflows can create guided forms and multi-step interfaces
  • Product teams exploring AI features gain a standardized way to build interactive experiences

Competitive Implications

Companies that adopt interactive MCP tools early can differentiate through superior user experience. While competitors are still copying and pasting text outputs, early adopters will be presenting live dashboards, interactive reports, and guided workflows. For OC's tech-forward industries — medtech, aerospace, logistics — this could mean the difference between AI as a novelty and AI as a competitive advantage.

Real-World Applications

Use Case 1: Healthcare Data Visualization

Scenario: A medtech startup in Irvine needs to analyze patient outcome data during daily team reviews

How This Helps: Instead of asking an AI to "describe the trends" and getting paragraphs of text, the team can invoke an MCP tool that renders an interactive dashboard showing patient cohorts, treatment outcomes, and statistical significance — all within their AI chat interface. Team members can hover for details, filter by demographics, and export specific views.

Example: A clinical operations manager asks, "Show me this quarter's patient retention by treatment protocol" and receives an interactive chart they can filter and annotate in real-time, without switching to a separate BI tool.

Use Case 2: Financial Configuration & Settings

Scenario: An Orange County financial services firm uses AI to help advisors configure investment portfolio strategies

How This Helps: Rather than describing complex allocation rules through text prompts, the AI can present an interactive configuration panel where advisors adjust sliders for risk tolerance, select asset classes from checkboxes, and see real-time impact on projected returns. The MCP tool collects all settings in one structured interaction.

Example: A wealth advisor says "Set up a growth portfolio for a 35-year-old client" and receives an interactive form with risk assessments, allocation options, and compliance checkboxes — all validated before submission.

Use Case 3: E-commerce Analytics for Brands

Scenario: An OC-based DTC brand wants to understand daily sales performance and inventory needs

How This Helps: Their custom MCP server can deliver an interactive sales dashboard showing revenue by channel, inventory alerts, and customer acquisition costs — all accessible by simply asking their AI assistant. Marketing and operations teams can drill into specific products or regions without learning new analytics tools.

Example: The operations lead asks "What's moving today?" and gets an interactive view of top-selling products, low-stock alerts, and regional performance — clickable, filterable, and ready to share with the team.

Local Angle

Opportunities for OC Businesses

  • Medtech & Healthcare: Build HIPAA-compliant interactive dashboards for patient data review and clinical decision support within AI assistants
  • Aerospace & Manufacturing: Create interactive quality control interfaces that let engineers visualize defect patterns and inspection data through conversational queries
  • Professional Services: Deliver interactive client reports, contract configuration tools, and compliance checklists through AI interfaces your teams already use
  • Retail & Hospitality: Build inventory management panels, guest feedback visualizations, and operational dashboards accessible via natural language

Getting Started

For developers:

  1. Review the SEP-1865 specification and early access SDK
  2. Experiment with the MCP-UI SDKs to build prototype interfaces
  3. Join the #ui-wg channel in the MCP Contributors Discord to connect with other builders

For business leaders:

  1. Identify workflows where your team currently struggles with text-only AI outputs
  2. Consider where interactive forms, dashboards, or visualizations would improve AI adoption
  3. Connect with developers in the OCAI community to explore proof-of-concept implementations

Discussion Questions

Prompts for deeper thinking:

  1. User experience implications: How might interactive interfaces change the way your team adopts AI tools? Would your employees prefer conversational access to dashboards over traditional BI tools?
  2. Security considerations: The spec emphasizes sandboxed iframes and user consent for tool calls. What security requirements would your organization need for interactive AI interfaces accessing internal data?
  3. Future possibilities: If AI assistants can render interactive UIs, what becomes possible in your industry that wasn't feasible with text-only interactions? Could this unlock new business models or customer experiences?

💭 We want to hear from you: Are you building MCP tools for your organization? What kinds of interactive interfaces would transform your workflows? Share your thoughts in the comments or bring your use cases to our next OCAI event.

Continue the Conversation

Want to explore MCP and agentic AI with other OC developers and business leaders?

Stay ahead of AI trends

Further reading: