Prospect Research Server

Provide tools and prompts to assist with prospect research tasks. Leverage built-in capabilities to calculate metrics, fetch information, and review code efficiently. Enhance your research workflow with a simple and effective MCP server implementation.

Installation

Installing for Claude Desktop

Manual Configuration Required

This MCP server requires manual configuration. Run the command below to open your configuration file:

npx mcpbar@latest edit -c claude

This will open your configuration file where you can add the Prospect Research Server MCP server manually.

Visit Prospect Research Server

Prospect Research MCP Server

smithery badge

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

Share:
Details:

  • Stars

    1

  • Forks

    2

  • Last commit

    4 months ago

  • Repository age

    4 months
View Repository

Auto-fetched from GitHub .

MCP servers similar to Prospect Research Server:

 

 
 

  • Stars

  • Forks

  • Last commit

 

 
 

  • Stars

  • Forks

  • Last commit

 

 
 

  • Stars

  • Forks

  • Last commit

Prospect Research Server: MCP Server – MCP.Bar