MCP server that provides unified access to multiple search services for model-context usage, enabling simplified querying and retrieval of context from Tavily, Brave, Kagi, Exa AI, GitHub, Linkup, and Firecrawl through four consolidated tools.
๐ ๏ธ Key Features
Unified MCP server interface for multiple search backends
Four consolidated tool endpoints for streamlined access
Compatibility with Model Context Protocol (MCP) workflows
Readme excerpt highlights integration and builds (Vite-based stack)
GitHub-hosted project with supporting badges and documentation
๐ Use Cases
Retrieve contextual information from diverse search providers via MCP
Enhance LLM reasoning with consolidated model-context sources
Quick integration into AI assistants needing multi-source search results
Simplified tooling for exploring Tavily, Brave, Kagi, Exa AI, GitHub, Linkup, and Firecrawl
โก Developer Benefits
Clear, single-server entry point for multiple backends
Focused MCP compatibility to speed up integration
Lightweight, vite-based tooling and test coverage guidance
Documentation-friendly readme excerpt for onboarding
โ ๏ธ Limitations
Based on provided readme excerpt and described integrations; specifics per backend may vary
Ensure proper API keys and access permissions for each integrated service
Potential latency from multi-provider aggregation depending on queries
A Model Context Protocol (MCP) server that provides unified access to
Tavily, Brave, Kagi, Exa AI, GitHub, Linkup, and Firecrawl through
four consolidated tools.
Search controls apply when supported by the selected provider.
ai_search
Get sourced AI answers with Kagi FastGPT, Exa Answer, Linkup, or
Tavily Research. Tavily Research returns a task ID first; pass it back
as research_id to retrieve the report.
json
{"query":"Explain the differences between REST and GraphQL","provider":"kagi_fastgpt"}