A WebMCP-powered mock interview application that allows an AI agent to conduct interactive interviews using tools exposed directly by the web application.
The user first provides their profile, then the AI agent can start and manage the interview through WebMCP tools. The user answers questions through the web interface, while the application tracks the interview phase, transcript, and final feedback.
- Harsh Nahar
- Tejas Dharmendra Patel
- Prantik Sarkar
- 👤 Candidate profile setup
- 🤖 AI-powered mock interviews
- 🔌 WebMCP tool integration
- 💬 Interactive interview experience
- 📝 Answer submission and transcript tracking
- 📊 Interview summary and feedback
- 🔍 Developer inspector for debugging WebMCP tools
- ⚡ Modern responsive web interface
Preparing for interviews can be difficult without having someone available to conduct a realistic interview.
We wanted to build an experience where an AI agent could interact directly with a web application instead of simply generating text in a chat.
This led us to explore WebMCP and build a mock interview platform where the AI agent can use tools exposed by the webpage to control the interview experience.
The application follows a simple interview workflow:
- The candidate enters their profile information.
- The profile is saved in the application.
- The AI agent connects to the WebMCP tools exposed by the webpage.
- The agent starts the mock interview.
- The candidate answers questions through the interface.
- The interview progresses through multiple questions.
- The application maintains the interview transcript.
- At the end, the candidate receives a summary and feedback.
The application has three main phases:
profile— Candidate profile setupin_progress— Active interviewreview— Interview summary and feedback
Mock Interview Coach is an interactive interview platform that combines AI with WebMCP to create a realistic mock interview experience.
Instead of simply chatting with an AI, the AI agent can interact with the web application through tools exposed by the page.
The candidate provides their profile, starts an interview through the AI agent, answers questions through the web interface, and receives a final interview summary and feedback.
One of the main parts of this project is the WebMCP integration.
The application registers its WebMCP tools using:
We plan to continue improving Mock Interview Coach by adding more interview scenarios, role-specific questions, advanced AI feedback, performance analytics, and additional WebMCP-powered capabilities.
Our goal is to make interview preparation more interactive, realistic, and accessible by combining AI agents with web applications.