Meeting Transcript Analyzer - Multi-Agent MCP App

A multi-agent system that analyzes meeting transcripts using AI-powered summarization, key point extraction, and task identification.

Features

• Summarize: Generate concise summaries of meeting transcripts (see screenshots)
• Key Highlights: Extract and display key points as bullet points (•) (see screenshots)
• Grab Tasks: Identify actionable tasks from meeting discussions (see screenshots)
• Modern Web UI: Clean, responsive horizontal layout interface for easy interaction

Prerequisites

• Python 3.9+
• OpenAI API key

Setup

1. Install dependencies:

   pip install -r requirements.txt
   

2. Configure OpenAI API Key: Create a file named openai_key.txt in the project root and add your OpenAI API key:

   sk-your-openai-api-key-here
   

Running the Agents

Important: All commands must be run from the project root directory.

Note: Start the sub-agents first, then the super agent to ensure proper tool registration.

1. Start the Summarizer Agent (Port 8001)

python3 -m uvicorn agents.summarizer_agent:summarizer_app --reload --port 8001

2. Start the Task Extractor Agent (Port 8002)

python3 -m uvicorn agents.task_extractor_agent:task_app --reload --port 8002

3. Start the Super Agent (Port 8000)

python3 -m uvicorn agents.super_agent:super_app --reload --port 8000

Using the Application

1. Access the Web Interface: Open your browser and go to: http://localhost:8000

2. Analyze a Transcript:

   • Paste your meeting transcript in the left textarea
   • Enter a prompt like "Summarize this meeting" or "Extract key points" in the second textarea
   • Click "Analyze Transcript"

3. View Results:

   • Results appear in the right panel with structured formatting
   • Summaries appear as formatted paragraphs
   • Key points display as clean bullet points (•)
   • Tasks show as numbered actionable items
   • Metadata shows transcript length, tool used, and point/task counts

Application Screenshots

Welcome Page

The clean, modern interface users see when first opening the application.

Summarize Flow

The application summarizing a meeting transcript with a brief, concise style.

Key Highlights Flow

Extracting key insights and main points from a meeting transcript as bullet points.

Task Extraction Flow

Identifying and extracting actionable tasks from meeting discussions.

Architecture

• Super Agent (Port 8000): Main entry point that serves the web UI and orchestrates sub-agents
• Summarizer Agent (Port 8001): Handles transcript summarization and key point extraction
• Task Extractor Agent (Port 8002): Identifies and extracts actionable tasks from transcripts

Technical Details

• Backend Formatting: All response formatting is handled by the super agent for consistent UI presentation
• Structured Responses: Responses include type, title, content, and metadata fields
• MCP Protocol: Uses Model Context Protocol for agent communication
• Responsive Design: UI adapts to mobile devices with vertical stacking

API Endpoints

• Super Agent: http://localhost:8000/ (Web UI) and /ask (API)
• Summarizer Agent: http://localhost:8001/docs (API docs)
• Task Extractor Agent: http://localhost:8002/docs (API docs)

Troubleshooting

• "ModuleNotFoundError: No module named 'agents'": Make sure you're running commands from the project root directory
• "uvicorn: command not found": Use python3 -m uvicorn instead of just uvicorn
• API Key Issues: Ensure openai_key.txt exists and contains a valid OpenAI API key
• Port Conflicts: Make sure ports 8000, 8001, and 8002 are available

Development

Code Formatting

To maintain consistent code style, use the provided formatting script:

python3 format_code.py

This will format all Python files with Black and HTML/Markdown files with Prettier.

Manual Formatting

You can also format files individually:

# Format Python files
python3 -m black agents/ --line-length=88

# Format HTML and Markdown files
prettier --write index.html README.md

File Structure

mcps/
├── agents/
│   ├── __init__.py
│   ├── summarizer_agent.py
│   ├── task_extractor_agent.py
│   ├── super_agent.py
│   ├── models.py
│   ├── config.py
│   └── utils.py
├── docs/
│   └── images/
│       ├── welcome-page.png
│       ├── summarize-flow.png
│       ├── key-highlights-flow.png
│       └── task-extraction-flow.png
├── index.html
├── requirements.txt
├── README.md
├── format_code.py
└── openai_key.txt (create this file)