A comprehensive research agent powered by Bright Data's advanced web scraping and data collection tools. Specializes in SEO research, competitor analysis, e-commerce insights, market trends, keyword research, SERP analysis, product monitoring, price tracking, and content optimization.

• Advanced Web Scraping: Access to Bright Data's premium web scraping infrastructure
• Dual AI Agents: Choose between LangGraph (with memory) or ADK (with extended timeouts)
• Slack Integration: Interactive chat interface with agent selection
• SEO Research: Comprehensive keyword research, SERP analysis, and competitor insights
• E-commerce Intelligence: Product monitoring, price tracking, and market analysis
• Actionable Insights: Structured data extraction and business intelligence

• Framework: LangChain + LangGraph
• Model: OpenAI GPT (configurable)
• Memory: Persistent conversation memory with checkpointer
• Timeout: Standard MCP timeout (5 seconds)
• Best For: Interactive conversations requiring context retention

• Framework: Google's Agent Development Kit (ADK)
• Model: Gemini 2.0 Flash
• Memory: Context-aware (last 5 messages)
• Timeout: Extended timeout (60 seconds) for complex operations
• Best For: Long-running web scraping and data collection tasks

1. Bright Data Account: Sign up at brightdata.com
2. Bright Data MCP Server: Documentation at github.com/brightdata/brightdata-mcp
3. OpenAI API Key: Get from platform.openai.com
4. Google AI API Key: Get from makersuite.google.com
5. Slack Workspace: Admin access to create Slack apps

1. Clone the repository

   git clone https://github.com/hollaugo/tutorials.git
   cd tutorials/bright-mcp-server-overview

2. Install dependencies

   pip install -r requirements.txt

3. Set up environment variables

   cp .env.example .env
   # Edit .env with your actual API keys

4. Install Bright Data MCP server

   npm install -g @brightdata/mcp

1. Go to api.slack.com/apps
2. Click "Create New App" → "From an app manifest"
3. Select your workspace
4. Copy and paste the content from slack_app_manifest.json
5. Click "Create"

1. Go to "OAuth & Permissions" in your app settings
2. Add the following Bot Token Scopes:

   assistant:write
   chat:write
   im:history
   files:write
   canvases:write
   

3. Click "Install to Workspace"
4. Copy the Bot User OAuth Token (starts with xoxb-)

For local development:

1. Go to "Socket Mode" in your app settings
2. Enable Socket Mode
3. Generate an App-Level Token with connections:write scope

1. Go to "Event Subscriptions"
2. Enable Events
3. Set Request URL to: https://your-domain.com/slack/events
4. Subscribe to these bot events:

   assistant_thread_started
   assistant_thread_context_changed
   message.im
   

1. Go to "App Settings" → "Agents & AI Apps"
2. Enable the feature
3. Configure your assistant settings

Update your .env file with the obtained values:

# Bright Data API Configuration
BRIGHTDATA_API_KEY=your_brightdata_api_key_here

# OpenAI Configuration (for LangGraph agent)
OPENAI_API_KEY=your_openai_api_key_here

# Google AI Configuration (for ADK agent)  
GOOGLE_API_KEY=your_google_api_key_here

# Slack Bot Configuration
SLACK_BOT_TOKEN=xoxb-your-slack-bot-token-here
SLACK_SIGNING_SECRET=your_slack_signing_secret_here

# Server Configuration
PORT=8010

python -m slack_app.slack_client

The server will start on the configured port (default: 8010).

1. Start a conversation with your bot in Slack
2. Select an AI agent from the dropdown:
   • LangGraph (Current): For conversations requiring memory
   • ADK (New): For complex data collection tasks
3. Ask your questions: The bot will use Bright Data's tools to research and respond

SEO Research:

• "Analyze the top 10 search results for 'best SEO tools 2024'"
• "What are the trending keywords in the digital marketing space?"
• "Compare the SEO strategies of competitor websites"

E-commerce Intelligence:

• "Track pricing trends for iPhone 15 across major retailers"
• "Analyze product reviews for wireless headphones on Amazon"
• "Monitor competitor inventory levels for gaming laptops"

Market Research:

• "What are the latest trends in sustainable fashion?"
• "Analyze social media sentiment around electric vehicles"
• "Research emerging technologies in the fintech space"

bright-mcp-server-overview/
├── adk_agent/                    # Google ADK agent implementation
│   ├── __init__.py
│   ├── agent.py                  # Main ADK agent with extended timeout
│   └── custom_adk_patches.py     # Timeout fixes for MCP connections
├── langgraph_agent/              # LangGraph agent implementation  
│   ├── __init__.py
│   └── agent.py                  # Main LangGraph agent with memory
├── slack_app/                    # Slack integration
│   └── slack_client.py           # Slack bot server and handlers
├── .env.example                  # Environment variables template
├── .gitignore                    # Git ignore rules
├── README.md                     # This file
├── requirements.txt              # Python dependencies
└── slack_app_manifest.json       # Slack app configuration

The ADK agent includes custom timeout patches to handle long-running operations:

• Default MCP Timeout: 5 seconds
• ADK Extended Timeout: 60 seconds
• Configurable: Modify timeout parameter in adk_agent/agent.py

The LangGraph agent includes persistent memory:

• Storage: In-memory with MemorySaver checkpointer
• Context Length: Automatically trimmed to last 20 messages
• Thread-based: Each Slack thread maintains separate memory

LangGraph Agent:

model = ChatOpenAI(model="o3")  # Change model here

ADK Agent:

model='gemini-2.0-flash-exp'  # Change model here

1. MCP Connection Timeout

   • Ensure Bright Data API key is valid
   • Check network connectivity
   • Try the ADK agent for longer operations

2. Slack Events Not Received

   • Verify webhook URL is accessible
   • Check event subscription configuration
   • Ensure bot has required permissions

3. Memory Not Working

   • Verify thread_id is being passed correctly
   • Check MemorySaver configuration
   • Try restarting the server

Enable detailed logging by setting:

import logging
logging.basicConfig(level=logging.DEBUG)

1. Fork the repository
2. Create a feature branch: git checkout -b feature-name
3. Commit changes: git commit -am 'Add feature'
4. Push to branch: git push origin feature-name
5. Submit a Pull Request

This project is licensed under the MIT License - see the LICENSE file for details.

• Bright Data Platform: brightdata.com
• Bright Data MCP Server: github.com/brightdata/brightdata-mcp
• LangGraph Documentation: langchain-ai.github.io/langgraph
• Google ADK: developers.google.com/ai/adk
• Slack API: api.slack.com

For issues related to:

• Bright Data MCP Server: Bright Data Support or GitHub Issues
• This Implementation: Create an issue in this repository
• Slack API: Slack API Documentation

Built with ❤️ using Bright Data, LangGraph, Google ADK, and Slack