MCPs tagged with search
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Brave Search MCP Server
MCP-compliant server providing advanced Brave Search API tools via STDIO and HTTP.
Implements a Model Context Protocol (MCP) server for integrating with the Brave Search API, offering tools for web, local business, image, video, and news searches along with AI-powered summarization. Supports both STDIO and HTTP transports and adheres to established MCP conventions for context management. Provides structured tool schemas and customizable parameters to handle sophisticated search queries and results. Enables advanced filtering, multi-type result aggregation, and seamless integration for AI model workflows.
- ⭐ 337
- MCP
- brave/brave-search-mcp-server
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Brave Search MCP Server
MCP integration for web, image, news, video, and local search via Brave Search API.
Implements a Model Context Protocol server that connects with the Brave Search API, enabling AI systems to perform comprehensive web, image, news, video, and local points of interest searches. Provides standardized MCP tools for various search types, each supporting advanced filtering parameters. Designed for easy integration in context-aware model interfaces such as Claude Code.
- ⭐ 86
- MCP
- mikechao/brave-search-mcp
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Search1API MCP Server
MCP server enabling search and crawl functions via Search1API.
Search1API MCP Server is an implementation of the Model Context Protocol (MCP) that provides search and crawl services using the Search1API. It allows seamless integration with MCP-compatible clients, including LibreChat and various developer tools, by managing API key configuration through multiple methods. Built with Node.js, it supports both standalone operation and Docker-based deployment for integration in broader AI toolchains.
- ⭐ 157
- MCP
- fatwang2/search1api-mcp
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VikingDB MCP Server
MCP server for managing and searching VikingDB vector databases.
VikingDB MCP Server is an implementation of the Model Context Protocol (MCP) that acts as a bridge between VikingDB, a high-performance vector database by ByteDance, and AI model context management frameworks. It allows users to store, upsert, and search vectorized information efficiently using standardized MCP commands. The server supports various operations on VikingDB collections and indexes, making it suitable for integrating advanced vector search in AI workflows.
- ⭐ 3
- MCP
- KashiwaByte/vikingdb-mcp-server