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Multi Chat MCP Server (Google Chat)

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Connect AI assistants like Cursor to Google Chat and beyond — enabling smart, extensible collaboration across chat platforms.

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#automation#slack#voice#cloud#devops#git#security#monitoring

Multi-Chat MCP Server (Google Chat Included)

<div align="center"> <p style="background-color: #f8f9fa; padding: 15px; border-radius: 5px; border-left: 5px solid #4285f4; max-width: 800px; margin: 0 auto;"> <strong>🔥 UNIQUE FEATURE:</strong> Run <strong>multiple chat providers simultaneously</strong> with a single AI assistant!<br> Your AI can interact with Google Chat, Slack, Teams, and more—all at once. <br> Ask once: <em>"Share this update with both Slack and Google Chat teams"</em><br> <a href="#running-multiple-chat-providers-simultaneously">➡️ Learn more about multi-provider capabilities</a> </p> </div> <div align="center"> <h3>Multi-Chat MCP Server is an open-source Python framework to build AI-powered chat integrations. Ships with full Google Chat support.</h3> <p> <strong>Keywords:</strong> Google Chat MCP • MCP Server Implementation • AI Chat Integration • Google Workspace Automation • Team Collaboration AI </p> </div>

🎯 What is Google Chat MCP Server?

Google Chat MCP Server is an open-source, production-ready Model Control Protocol (MCP) server designed for Google Chat integration with AI assistants. Built with an extensible multi-provider architecture, this project provides a robust foundation for integrating AI assistants with team chat platforms.

🏢 Built for Organizational Security & Privacy

Important Security Note: This tool is designed for local, organizational use only. We strongly recommend using this with organization-provided on-premises LLM instances or your local installed LLM Agent Model rather than cloud-based LLM model's to maintain complete control over your team's chat data and communications.

Why Local/On-Premises Deployment:

  • Data Privacy: Keep sensitive team conversations within your organization
  • Security Compliance: Meet enterprise security and compliance requirements
  • Full Control: Maintain complete oversight of data flow and access
  • Custom Policies: Implement organization-specific security measures

While anyone can adapt this tool for their particular use cases, it's designed with enterprise security as a priority.

Current Implementation Status

  • ✅ Google Chat Provider - Production Ready with comprehensive API coverage
  • 🔄 Slack Provider - Planned (contributions welcome)
  • 📝 Microsoft Teams Provider - Planned (contributions welcome)

Key Capability: All providers can run simultaneously with a unified interface, allowing your AI assistant to seamlessly work across multiple chat platforms at once. Learn more about this powerful feature.

🧭 The Story Behind This Project

We even see open-source MCP servers for Google Chat — but not sure about Microsoft Teams or Slack, officially or in open source. However, even the ones that do exist fall short in real-world applicability. They offer limited functionalities that cannot handle full-context workflows like this project demonstrates.

This multi-provider MCP framework was born from a real frustration experienced by development teams trying to leverage AI assistants in their daily workflows.

The Original Problem

Picture this scenario: You're debugging a complex issue, your AI assistant suggests a solution, but you need to check if your teammates have encountered something similar. You switch to Google Chat, scroll through hundreds of messages, copy-paste error logs, wait for responses, then manually relay the solution back to your AI assistant.

This constant context-switching was breaking the flow of productive AI-assisted development.

The Breaking Point

During a critical production incident, a developer spent 30 minutes manually shuttling information between Claude (via Cursor) and the team's Google Chat space. The AI had the technical knowledge to help. The team had the contextual experience. But there was no bridge connecting these two knowledge sources.

That's when we realized:

AI assistants need to be participants in team collaboration — not isolated tools.

Our Solution:

  • Seamless Integration: AI assistants become active participants in team chat
  • Contextual Awareness: AI can search team history for similar issues and solutions
  • Collaborative Problem-Solving: AI can share problems with the team and implement their suggestions
  • Knowledge Bridging: Connect AI technical knowledge with team experiential knowledge

🎯 Built for Developer Extensibility

🏗️ Modular Provider Architecture

Each chat platform is implemented as an independent module:

src/providers/
├── google_chat/     # ✅ Complete implementation
├── slack/           # 📋 Framework ready for implementation  
└── teams/           # 📋 Framework ready for implementation

👥 Who's This For?

This project is designed for two primary audiences:

🛠️ 1. Developers inside organizations

If you're a developer working in a team that uses Google Chat, and you're looking to integrate your AI IDEs (like Cursor, CodeWhisperer, or Copilot Chat) with team conversations — this MCP client will save you hours. No more manually copying logs, checking for context, or waiting for someone to see your question. Your AI agent can now directly:

  • Search your chat history for relevant past discussions
  • Share code snippets or error logs automatically
  • Receive responses and convert them into actionable fixes
  • Summarize ongoing team activities
  • Fetch missing config/scripts from shared spaces

💡 2. Open source contributors & AI platform builders

If you're building AI-powered tools, IDE integrations, or internal assistants — this is your starting point for a multi-provider MCP architecture. You can fork this project to:

  • Extend support for Slack, Microsoft Teams, or custom messaging platforms
  • Build your own custom AI workflows on top of MCP

Google Chat Tools Supported (will be extended)

Interact with Google Chat using the tools below. Each tool includes its source file and parameters.

🧭 Space Management

  • get_chat_spaces_tool – List spaces
  • manage_space_members_tool – Add/remove members
  • get_conversation_participants_tool – Get space participants
  • summarize_conversation_tool – Summarize conversation

💬 Messaging

  • send_message_tool – Send a message
  • reply_to_message_thread_tool – Reply in thread
  • update_chat_message_tool – Update message
  • delete_chat_message_tool – Delete message

😀 Interactions

  • add_emoji_reaction_tool – React to message
  • get_chat_message_tool – Get message details

🔍 Search & Filters

  • search_messages_tool – Search messages
  • get_my_mentions_tool – Find mentions

👤 User Info

  • get_my_user_info_tool – Your profile
  • get_user_info_by_id_tool – User by ID
  • get_message_with_sender_info_tool – Message with sender info
  • list_messages_with_sender_info_tool – List messages with sender info

📎 File Handling

  • upload_attachment_tool – Upload attachment
  • send_file_message_tool – Send file content
  • send_file_content_tool – Send formatted file content

📦 Batch Operations

  • batch_send_messages_tool – Send multiple messages

📁 Source files located under src/providers/google_chat/tools/

🔥 Real-World Workflows Enabled

The demo walkthrough above demonstrates these practical team collaboration workflows:

Collaborative Problem Solving

  • Error Sharing & Resolution: AI shares developer errors with team, receives expert guidance, and implements solutions
  • Knowledge Transfer: Team expertise is captured and applied through AI assistance
  • Proactive Issue Detection: AI monitors team chat for emerging concerns and offers assistance

Intelligent Resource Management

  • Script Exchange: Request and receive team scripts with automatic comparison to local versions
  • Requirements Synchronization: Pull and merge requirements files from team discussions
  • Context-Aware Sharing: AI determines optimal file sharing based on team needs

Enhanced Team Communication

  • Mention Tracking: Comprehensive monitoring and response to team mentions
  • Activity Summaries: AI-generated updates on team progress and blockers
  • Semantic Search: Find conceptually related discussions across team spaces

📁 Project Architecture

multi-chat-mcp-server/
├── src/
│   ├── providers/
│   │   ├── google_chat/           # ✅Production-Ready Google Chat MCP
│   │   │   ├── api/               # Google Chat API implementation
│   │   │   ├── tools/             # MCP tools for Google Chat
│   │   │   ├── utils/             # Utilities and helpers
│   │   │   ├── README.md          # Setup guide
│   │   │   └── CURSOR_INTEGRATION.md  # Cursor integration
│   │   ├── slack/                 # 📋 Ready for implementation
│   │   └── teams/                 # 📋 Ready for implementation
│   ├── mcp_core/                  # Core MCP functionality
│   └── server.py                  # Multi-provider MCP server
├── provider-config.yaml           # Provider configurations
└── google_chat_mcp_client_demo_images/  # Demo screenshots

Provider Configuration

providers:
  google_chat:
    name: "Google Chat MCP Server"
    description: "Production-ready Google Chat MCP integration"
    token_path: "src/providers/google_chat/token.json"
    credentials_path: "src/providers/google_chat/credentials.json"
    callback_url: "http://localhost:8000/auth/callback"

🔮 Roadmap & Contributing

Current Implementation Status

  • ✅ Google Chat Provider - Production ready with comprehensive features
  • 📋 Slack Provider - Framework ready, implementation needed
  • 📋 Teams Provider - Framework ready, implementation needed

How to Contribute

We welcome contributions to extend this framework with additional providers:

  1. Choose a Provider: Slack, Teams, or any other chat platform
  2. Follow the Architecture: Use src/providers/google_chat/ as a reference
  3. Implement Core Features: Messages, search, user management
  4. Add Provider-Specific Tools: Leverage unique platform capabilities
  5. Submit Pull Request: We'll help review and integrate

Getting Started with Contributions:

📚 Documentation

Essential Resources

🏆 Why Choose This MCP Server?

✅ Battle-Tested Google Chat Integration

  • Comprehensive API coverage beyond basic messaging
  • Real-world workflows tested in development environments
  • Production-ready with proper error handling and authentication

✅ Developer-Friendly Architecture

  • Created by developers for actual development workflows
  • Modular design makes it easy to understand and extend
  • Well-documented with practical examples

✅ Community-Extensible Framework

  • Open source with transparent development
  • Contributor-friendly architecture and documentation
  • Multi-provider ready for diverse business needs

📞 Support & Community

Get Help

Contributing

We welcome contributions to expand this multi-provider framework:

  1. Fork the repository
  2. Create a feature branch for your provider or enhancement
  3. Follow the existing architecture patterns
  4. Submit a pull request
  5. Sign our Contributor License Agreement

📄 License & Copyright

Open Source License

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

Copyright Notice

Copyright (c) 2025 Sivaprakash Kumar. All rights reserved.

While this is an open-source project welcoming contributions, all copyright and ownership rights remain with Sivaprakash Kumar. See COPYRIGHT for details.

<div align="center"> <h3>🚀 Start Building with Google Chat MCP Server Today!</h3> <p> <strong>Production-ready Google Chat integration with extensible multi-provider architecture</strong><br> Perfect for developers building AI-powered team collaboration tools </p> <p> <strong>⭐ Star this repository if it helps your development workflow!</strong><br> <strong>🤝 Contribute to expand support for Slack, Teams, and other platforms!</strong> </p> </div>