MCP Research Server MCP Server

Local setup required. This server has to be cloned and prepared on your machine before you register it in Claude Code.
1

Set the server up locally

Run this once to clone and prepare the server before adding it to Claude Code.

Run in terminal
pip install -r requirements.txt
2

Register it in Claude Code

After the local setup is done, run this command to point Claude Code at the built server.

Run in terminal
claude mcp add -e "OPENAI_API_KEY=${OPENAI_API_KEY}" mcp-research-server -- python "<FULL_PATH_TO_MCP2_TEST>/dist/index.js"

Replace <FULL_PATH_TO_MCP2_TEST>/dist/index.js with the actual folder you prepared in step 1.

Required:OPENAI_API_KEY
README.md

An intelligent company research and competitive analysis tool

šŸ” Company Research Agent with MCP + OpenAI + Gradio

An intelligent company research and competitive analysis tool that combines the power of Model Context Protocol (MCP), OpenAI GPT-4, and Gradio to deliver comprehensive business intelligence.

🌟 Features

  • Automated Company Research: Search for company information using MCP tools
  • Competitor Analysis: Automatically identify and analyze competitors
  • Business Model Analysis: Understand company operations and revenue streams
  • Market Keywords Extraction: Extract relevant keywords describing the competitive landscape
  • AI-Powered Insights: OpenAI synthesizes research into actionable executive summaries
  • Interactive UI: Beautiful Gradio interface for easy interaction

šŸ—ļø Architecture

ā”Œā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”
│  Gradio UI      │
│  (Frontend)     │
ā””ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”¬ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”˜
         │
         ā–¼
ā”Œā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”      ā”Œā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”
│  OpenAI GPT-4   │◄────►│  MCP Server      │
│  (AI Analysis)  │      │  (Research Tools)│
ā””ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”˜      ā””ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”˜
                                   │
                         ā”Œā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”“ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”
                         │  Research Tools:  │
                         │  • Company Info   │
                         │  • Competitors    │
                         │  • Business Model │
                         │  • Keywords       │
                         ā””ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”˜

šŸ“‹ Components

1. MCP Research Server (`mcp_research_server.py`)

FastMCP server providing research tools:

  • search_company_info() - Search for basic company information
  • find_competitors() - Find competitor companies
  • analyze_company_business() - Analyze business model and activities
  • extract_market_keywords() - Extract market and industry keywords
  • generate_competitive_report() - Generate full competitive analysis

2. Gradio Application (`gradio_app.py`)

Interactive web interface that:

  • Accepts company name and OpenAI API key as inputs
  • Orchestrates MCP tool calls for data gathering
  • Uses OpenAI to generate intelligent summaries
  • Displays results in an organized, user-friendly format

šŸš€ Quick Start

Prerequisites

Installation

  1. Clone or download this repository

  2. Run the setup script:

    chmod +x setup.sh
    ./setup.sh
    
  3. Configure your API key:

    cp .env.example .env
    # Edit .env and add your OpenAI API key
    

Manual Installation

If you prefer manual setup:

# Create virtual environment
python3 -m venv venv
source venv/bin/activate

# Install dependencies
pip install -r requirements.txt

šŸ’» Usage

Start the Application

# Activate virtual environment (if not already active)
source venv/bin/activate

# Run the Gradio app
python gradio_app.py

The application will start on http://localhost:7860

Using the Interface

  1. Enter a company name (e.g., "Apple", "Tesla", "Netflix")
  2. Enter your OpenAI API key (required for AI analysis)
  3. Click "Research Company" to start the analysis
  4. View results:
    • Executive Summary (AI-generated)
    • Full Report (expand accordion)
    • Market Keywords (expand accordion)

Example Companies to Try

  • Technology: Apple, Microsoft, Google, Amazon, Meta
  • Automotive: Tesla, Ford, General Motors
  • Entertainment: Netflix, Disney
  • Consumer Goods: Nike, Coca-Cola, Starbucks

šŸ“¦ Dependencies

  • fastmcp - Model Context Protocol server framework
  • gradio - Web UI framework
  • openai - OpenAI API client
  • requests - HTTP library for web requests
  • beautifulsoup4 - HTML parsing (for future web scraping)
  • python-dotenv - Environment variable management

šŸ”§ How It Works

  1. User Input: User enters company name in Gradio interface
  2. MCP Tools: Application calls MCP research tools to gather data:
    • Company information from Wikipedia API
    • Competitor identification from database
    • Business model analysis
    • Market keyword extraction
  3. AI Synthesis: OpenAI GPT-4 processes all research data and generates:
    • Executive summary
    • Key insights
    • Market positioning analysis
  4. Results Display: Formatted report shown in Gradio UI

šŸŽÆ Use Cases

  • Competitive Intelligence: Understand your competitors quickly
  • Market Research: Identify market trends and keywords
  • Investment Analysis: Research companies for investment decisions
  • Business Strategy: Inform strategic planning with competitive data
  • Sales Enablement: Prepare for sales conversations with prospect research

šŸ” Security Notes

  • Never commit your .env file or expose your OpenAI API key
  • Use environment variables for sensitive information
  • The .env.example file is provided as a template

šŸ› ļø Customization

Adding More Companies

Edit `mcp_r

Tools (5)

search_company_infoSearch for basic company information
find_competitorsFind competitor companies
analyze_company_businessAnalyze business model and activities
extract_market_keywordsExtract market and industry keywords
generate_competitive_reportGenerate full competitive analysis

Environment Variables

OPENAI_API_KEYrequiredAPI key for OpenAI GPT-4 analysis

Configuration

claude_desktop_config.json
{"mcpServers": {"research": {"command": "python", "args": ["/path/to/mcp_research_server.py"]}}}

Try it

→Research the business model and primary activities of Tesla.
→Find the main competitors for Netflix and analyze their market positioning.
→Extract the key market keywords for Apple to understand their current industry landscape.
→Generate a full competitive analysis report for Starbucks.

Frequently Asked Questions

What are the key features of MCP Research Server?

Automated company research using MCP tools. Automatic identification and analysis of competitors. Business model and revenue stream analysis. Market keyword extraction for competitive landscapes. AI-powered synthesis of research into executive summaries.

What can I use MCP Research Server for?

Quickly understanding the competitive landscape of a new industry. Identifying market trends and relevant keywords for business strategy. Conducting due diligence for investment analysis. Preparing for sales conversations with prospect research. Informing strategic planning with data-driven competitive insights.

How do I install MCP Research Server?

Install MCP Research Server by running: pip install -r requirements.txt

What MCP clients work with MCP Research Server?

MCP Research Server works with any MCP-compatible client including Claude Desktop, Claude Code, Cursor, and other editors with MCP support.

Turn this server into reusable context

Keep MCP Research Server docs, env vars, and workflow notes in Conare so your agent carries them across sessions.

Need the old visual installer? Open Conare IDE.
Open Conare