🗓️ Meeting Prep Agent

Download a full demo video by clicking here

👋 Welcome to the Tavily Meeting Prep Agent!

This repository demonstrates how to build a meeting preparation agent with real-time web access, leveraging Tavily's advanced search capabilities. This agent will connect to your Google Calendar via MCP, extract meeting information, and use Tavily search for profile research on the meeting attendees and general information on the companies you are meeting with.

The project is designed for easy customization and extension, allowing you to:

• Integrate proprietary or internal data sources
• Modify the agent architecture or swap out LLMs

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🚀 Features

• 🌐 Real-time Web Search: Instantly fetches up-to-date information using Tavily's search API.
• 🧠 Agentic Reasoning: Combines MCP and ReAct agent flows for smarter, context-aware responses.
• 🔄 Streaming Substeps: See agentic reasoning and substeps streamed live for transparency.
• 🔗 Citations: All web search results are cited for easy verification.
• 🗓️ Google Calendar Integration: (via MCP) Access and analyze your meeting data.
• ⚡ Async FastAPI Backend: High-performance, async-ready backend for fast responses.
• 💻 Modern React Frontend: Interactive UI for dynamic user interactions.

System Diagram

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📂 Repository Structure

• Backend (backend/)
  • agent.py: Agentic flow (MCP + LangChain-Tavily ReAct agent)
• Frontend (ui/): React-based UI for meeting insights
• Server (app.py): FastAPI server for API endpoints and streaming

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🛠️ Local Setup

Python version: 3.13.2 (local development)

Google Calendar MCP Setup

See google-calendar-mcp for full details.

Google Cloud Setup:

1. Go to the Google Cloud Console and create/select a project.
2. Enable the Google Calendar API.
3. Create OAuth 2.0 credentials:
   • Go to Credentials
   • Click "Create Credentials" > "OAuth client ID"
   • Choose "User data" for the type of data that the app will be accessing
   • Add your app name and contact information
   • Select "Desktop app" as the application type
4. Add your email as a test user under the OAuth Consent screen.
5. Create a file gcp-oauth.keys.json in the root of google-calendar-mcp directory.
6. Download your credentials and paste them in gcp-oauth.keys.json.

This file should look like:

{
  "installed": {
    "client_id": "<your-client-id>",
    "project_id": "<your-project-id>",
    "auth_uri": "<your-auth-uri>",
    "token_uri": "<your-token-uri>",
    "auth_provider_x509_cert_url": "<your-auth-provider>",
    "client_secret": "<your-secret>",
    "redirect_uris": ["http://localhost"]
  }
}

Install the MCP:

cd google-calendar-mcp
npm install

Set config path:

GOOGLE_CALENDAR_CONFIG=<absolute-path-to-project>/mcp-use-case/google-calendar-mcp/build/index.js

Run the notebook mcp-test.ipynb to check that your MCP setup is working before proceeding.

Backend Setup

1. Create and activate a virtual environment:

   python3 -m venv venv
   source venv/bin/activate  # On Windows: .\venv\Scripts\activate

2. Install dependencies:

   python3 -m pip install -r requirements.txt

3. Set environment variables:

   export TAVILY_API_KEY="your-tavily-api-key"
   export OPENAI_API_KEY="your-openai-api-key"
   export GROQ_API_KEY=<"your-groq-api-key>
   export GOOGLE_CALENDAR_CONFIG="<absolute-path-to-project>/mcp-use-case/google-calendar-mcp/build/index.js"

4. Run the backend server:

   python app.py

Frontend Setup

1. Navigate to the frontend directory:

   cd ui

2. Install dependencies:

   npm install

3. Start the development server:

   npm run dev

.env file example:

TAVILY_API_KEY=your-tavily-api-key
OPENAI_API_KEY=your-openai-api-key
GROQ_API_KEY=your-groq-api-key
GOOGLE_CALENDAR_CONFIG=your-google-config

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📡 API Endpoints

• POST /api/analyze-meetings: Handles streamed LangGraph execution

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🤝 Contributing

Feel free to submit issues and enhancement requests!

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📞 Contact

Questions, feedback, or want to build something custom? Reach out!

• Email: Dean Sacoransky

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