MCP SuperAssistant Chrome Extension: Ultimate Guide to Connect AI Assistants with Real-Time Data

MCP SuperAssistant Cover Image
Seamlessly integrate ChatGPT, Google Gemini, Perplexity, and more with data ecosystems using MCP tools.

Why Do You Need MCP SuperAssistant?

In the fast-evolving AI landscape, bridging the gap between AI assistants and enterprise data, development environments, or content repositories is critical for productivity. The Model Context Protocol (MCP), developed by Anthropic, is an open standard designed to connect AI systems with real-time data sources. The MCP SuperAssistant Chrome Extension takes this power further by integrating MCP tools directly into popular AI platforms like ChatGPT and Google Gemini.

Whether you’re a developer, data analyst, or casual user, this extension enables real-time data interaction, automated task execution, and smart result insertion within AI conversations. This guide explores its features, installation, use cases, and SEO tips to help you master this AI-enhancing tool.

Table of Contents

  1. Key Features of MCP SuperAssistant
  2. Supported AI Platforms
  3. How It Works: Architecture & Workflow
  4. Installation Guide: Chrome Store & Proxy Setup
  5. User Guide: Basics to Advanced Modes
  6. Developer Resources: Custom Tools & Integration
  7. SEO Tips & FAQs

1. Key Features of MCP SuperAssistant

1.1 Multi-Platform AI Integration

Works with ChatGPT, Google Gemini, Perplexity, Grok, AI Studio, and OpenRouter, with more platforms coming soon.

1.2 Smart Tool Detection & Execution

  • Auto-Detect Tools: Identifies MCP tool calls (e.g., database queries, API triggers) in AI-generated responses.
  • One-Click Execution: Run tools via the sidebar and insert results directly into chats.
  • Automation Modes: Enable Auto-Execute (tools run automatically) and Auto-Submit (results auto-send to chat).

1.3 User-Friendly Interface

  • Theme Adaptation: Matches dark/light modes of AI platforms.
  • Sidebar Design: Centralizes tool lists, server status, and settings without disrupting workflows.
  • Preferences Sync: Remembers sidebar position, size, and mode settings.

1.4 Security & Flexibility

  • Local Proxy Support: Securely connect to internal MCP servers with CORS compliance.
  • Health Monitoring: Track server status via proxy endpoints.

2. Supported AI Platforms

Currently compatible with:

  • ChatGPT: Enhance responses with real-time data.
  • Google Gemini: Integrate enterprise data for decision-making.
  • Perplexity: Improve fact-checking with dynamic queries.
  • Grok: Automate development tasks.
  • AI Studio & OpenRouter: Extend model training capabilities.

3. How It Works: Architecture & Workflow

3.1 The Role of Model Context Protocol (MCP)

MCP is an open communication protocol enabling AI systems to interact securely with:

  • Content Management Systems (e.g., Notion, Confluence)
  • Business Tools (e.g., Salesforce, Zapier)
  • Development Environments (e.g., GitHub, Docker)

This allows AI assistants to access live data instead of static datasets.

3.2 MCP SuperAssistant Workflow

AI Generates Tool Call → Extension Detects Call → Proxy Server → MCP Server → Results Inserted into Chat
  • SSE Communication: Uses Server-Sent Events for low-latency data transfer.
  • Local Proxy: Resolves CORS issues and provides debugging interfaces.

4. Installation Guide

4.1 Install from Chrome Web Store (Recommended)

  1. Visit the Chrome Web Store page.
  2. Click “Add to Chrome” → Confirm installation.

4.2 Configure Local Proxy Server

For internal MCP server connections:

# Start proxy via npx  
npx @srbhptl39/mcp-superassistant-proxy@latest --config ./mcptestconfig.json  

Use Cases:

  • Add CORS support to remote MCP servers.
  • Monitor server health.

4.3 Connection Steps

  1. Launch the proxy and open the extension sidebar on an AI platform.
  2. Click the server status icon → Enter http://localhost:3006.
  3. Click “Connect” to establish the link.

5. User Guide

5.1 Basic Operations

  1. Ask a question on ChatGPT (e.g., “Fetch last week’s sales data”).
  2. AI responds with an MCP tool call (e.g., <mcp:query_database table="sales" date="last_week"/>).
  3. The sidebar detects the tool → Click “Execute” → Results appear in the chat.

5.2 Advanced Modes

  • Push Content Mode: Send page content to AI instead of overlaying chats.
  • Multi-Server Switching: Connect to test and production environments simultaneously.

6. Developer Resources

6.1 Build Custom Tools

  1. Clone the repo and install dependencies:
git clone https://github.com/srbhptl39/MCP-SuperAssistant  
pnpm install && pnpm build  
  1. Modify tool logic in the src/tools directory.
  2. Load the unpacked extension in Chrome’s Developer Mode.

6.2 Tech Stack

  • Frontend: React + Vite.
  • Communication: SSE + RESTful APIs.
  • Proxy Service: Node.js + Express.

7. SEO Tips & FAQs

7.1 Keyword Optimization

  • Primary Keywords: MCP SuperAssistant, Model Context Protocol Tools, AI Assistant Integration.
  • Long-Tail Keywords: How to Connect MCP Proxy, ChatGPT Data Extension, Automate AI Tools.

7.2 Frequently Asked Questions

Q1: Is MCP SuperAssistant free?

  • Yes, but you need to deploy your own MCP server.

Q2: Does it support private networks?

  • Absolutely! Use the local proxy for internal server connections.

Q3: How to contribute to the project?

Conclusion

The MCP SuperAssistant Chrome Extension is a game-changer for developers and enterprises aiming to supercharge AI workflows. By following this guide, you’ve learned how to install, configure, and customize the tool. Download it from the Chrome Web Store or join the open-source community on GitHub!

Further Reading:

License: This article is published under the MIT License. Redistribution with attribution is encouraged.