[Self-hosted] A Model Context Protocol (MCP) server implementation that provides a web search capability over stdio transport. This server integrates with a WebSearch Crawler API to retrieve search results.
Overview
What is WebSearch-MCP?
WebSearch-MCP is a self-hosted Model Context Protocol (MCP) server that provides web search capabilities over stdio transport, integrating with a WebSearch Crawler API to retrieve real-time search results.
How to use WebSearch-MCP?
To use WebSearch-MCP, install it via npm or Smithery, configure the crawler service, and integrate it with your AI client applications to perform web searches.
Key features of WebSearch-MCP?
- Real-time web search capabilities for AI assistants.
- Integration with a Crawler API for retrieving search results.
- Customizable configuration through environment variables.
Use cases of WebSearch-MCP?
- Enabling AI models to fetch up-to-date information from the web.
- Assisting in research by providing relevant search results.
- Enhancing AI applications with real-time data retrieval.
FAQ from WebSearch-MCP?
- Can WebSearch-MCP be used with any AI model?
Yes! It can be integrated with any AI model that supports the Model Context Protocol.
- Is WebSearch-MCP easy to set up?
Yes! It provides detailed installation and configuration instructions.
- What are the prerequisites for running WebSearch-MCP?
You need Docker and Docker Compose to set up the crawler service.