MCP.so
Sign In

MarketScope AI: Healthcare Product Analytics

@BigDataTeam5

RepositoryHomepage

About MarketScope AI: Healthcare Product Analytics

This is our final project , in this we have utlized langgraph coupled with various mcp server mounted of fastapi using fastmcp to create mutlifaceted application for healthcare vendor to make them understand more about their product performance and provide suggestions and strateg

#airflow#mcp#snowflake#s3-bucket#gce#streamlit#serapi#langgraph#fastmcp

Basic information

Category

Data & Analytics

Runtime

python

Transports

stdio

Publisher

BigDataTeam5

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "MarketScope-AI-Powered-Industry-Segment-Intelligence-Platform": {
      "command": "python",
      "args": [
        "run_servers.py"
      ]
    }
  }
}

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is MarketScope AI: Healthcare Product Analytics?

MarketScope AI: Healthcare Product Analytics is an intelligent analytics platform that uses advanced AI and natural language processing to analyze healthcare market segments. It is designed for professionals who need to understand market segmentation, compare products, and gain AI-powered insights from sales and marketing data.

How to use MarketScope AI: Healthcare Product Analytics?

The platform requires Python 3.8 or higher. Start by running python run_servers.py for automatic dependency installation and server startup, or manually install requirements with pip install -r requirements.txt, then start the API server (python api/main.py) and the Streamlit frontend (streamlit run frontend/app.py). Deployed instances are also accessible via the listed HTTP endpoints.

Key features of MarketScope AI: Healthcare Product Analytics

  • Market Segmentation Analysis across multiple healthcare segments
  • Strategic Query Optimization for targeted question answering
  • Product Comparison across different market segments
  • Sales & Marketing Analysis with CSV upload for AI insights
  • Retrieval Augmented Generation (RAG) from marketing knowledge books

Use cases of MarketScope AI: Healthcare Product Analytics

  • Analyze market segments such as diagnostics, supplements, OTC pharmaceuticals, fitness wearables, and skin care
  • Compare healthcare products across segments to identify positioning opportunities
  • Upload sales data to receive AI-powered analysis and recommendations
  • Use RAG to get tailored marketing strategies from Kotler's Marketing Management book

FAQ from MarketScope AI: Healthcare Product Analytics

What exactly does MarketScope AI do?

It analyzes healthcare market segments using AI and NLP, provides product comparison, strategic query optimization, and sales data analysis, and includes a RAG system for marketing knowledge.

What are the runtime dependencies?

Python 3.8 or higher, plus required packages listed in requirements.txt (installed automatically when using run_servers.py).

Where does my data live?

You upload your sales data as a CSV file locally via the Streamlit interface. Sample data is also provided. Deployed servers are publicly accessible at the given HTTP endpoints.

What healthcare segments are supported?

Diagnostic, Supplement, OTC Pharmaceutical, Fitness Wearable, and Skin Care segments.

Is this server certified or deployed publicly?

Yes, it is certified by MCPHub and has multiple deployed MCP servers accessible at the URLs provided in the README.

Comments

More Data & Analytics MCP servers

Bright Data MCP

brightdata-com

A powerful Model Context Protocol (MCP) server that provides an all-in-one solution for public web access.

2.5K

PubMed Analysis MCP Server

Darkroaster

A PubMed MCP server.

150

PubMed MCP Server

cyanheads

Search PubMed/Europe PMC, fetch articles and full text (PMC/EPMC/Unpaywall), citations, MeSH terms via MCP. STDIO or Streamable HTTP.

121

Google Ads MCP

cohnen

An MCP tool that connects Google Ads with Claude AI/Cursor and others, allowing you to analyze your advertising data through natural language conversations. This integration gives you access to campaign information, performance metrics, keyword analytics, and ad management—all th

657

Google Analytics MCP Server

surendranb

Google Analytics 4 data to AI agents, agentic workflows, and MCP clients. Give agents analysis-ready access to website traffic, user behavior, and performance data with schema discovery, server-side aggregation, and safe defaults that reduce data wrangling.

225