What is Prospect Research Mcp

Prospect Research MCP is a Model Context Protocol server implementation designed for prospect research tools, deployed on the Smithery Web infrastructure.

Use cases

Use cases include conducting detailed market analysis, gathering information on potential clients or partners, performing competitive analysis, and supporting academic research projects.

How to use

To use prospect-research-mcp, configure the required API keys in the Smithery Web environment and integrate it with applications like Claude Desktop by adding it to the configuration file.

Key features

Key features include semantic search for contextual understanding, webpage scraping for content extraction, batch search processing for executing multiple queries in parallel, and comprehensive coverage through various search methods.

Where to use

Prospect-research-mcp can be utilized in fields such as market research, academic research, business development, and any area requiring in-depth prospect analysis.

Prospect Research MCP Server

A Model Context Protocol (MCP) server implementation focused on prospect research tools, deployed on Smithery Web infrastructure.

Features

• Semantic Search: Contextual search that understands meaning and intent behind queries
• Webpage Scraping: Extract and process content from multiple web pages
• Batch Search Processing: Execute multiple search queries in parallel
• Comprehensive Coverage: Combine different search approaches for thorough research

Tools

• web-search

  • A semantic search engine (Tavily) that understands the contextual meaning and intent behind queries
  • Inputs:
    • query (string): The search query to look up

• scrape-webpages

  • Scrape the provided web pages for detailed information
  • Inputs:
    • links (array): A list of URLs to scrape (optimally less than 10)
  • Processes content to remove images and returns combined content from provided URLs

• batch-web-search

  • Traditional keyword-based search (Google via Search1API) that processes multiple queries simultaneously
  • Inputs:
    • queries (array): List of search queries to process in parallel (optimally less than 30)
  • Executes multiple distinct search queries in parallel

Prompts

• simple-assist - A basic prompt for general queries
• research - A prompt for detailed research questions
• review-code - A prompt for code review

Configuration

Required API Keys

This server requires the following API keys:

• TAVILY_API_KEY - For semantic web search functionality
• JINA_API_KEY - For webpage scraping
• SEARCH1API_KEY - For batch web search

These are configured in the Smithery Web environment for the deployed version.

Usage with Claude Desktop

Add this to your claude_desktop_config.json:

{
  "mcpServers": {
    "prospect-research": {
      "transport": "sse",
      "url": "https://smithery.ai/server/@jzhang17/prospect-research-mcp",
      "env": {
        "TAVILY_API_KEY": "YOUR_TAVILY_API_KEY",
        "JINA_API_KEY": "YOUR_JINA_API_KEY",
        "SEARCH1API_KEY": "YOUR_SEARCH1API_KEY"
      }
    }
  }
}

For Other MCP Clients

Configure your client to connect to the server using the SSE transport type and the Smithery-hosted URL.

Structure

• /src/index.ts - Main server entrypoint
• /src/tools/ - MCP tool implementations (web search, webpage scraping, batch search)
• /src/prompts/ - MCP prompt implementations
• /src/types/ - TypeScript type definitions

Deployment

This server is deployed to Smithery Web platform. To access the deployed server:

1. Visit Smithery.ai
2. The server is available at the URL provided by Smithery Web

References

• Model Context Protocol
• MCP TypeScript SDK
• Smithery AI Platform
• MCP Client List