What does the server do?
It provides an AI search tool that fetches results from external search engines and internal knowledge bases, then feeds them into an AI model to improve answer quality.
@cr7258
Basic information
An MCP server enhances AI responses with real-time search results via Higress ai-search.
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"higress-ai-search-mcp-server": {
"command": "uvx",
"args": [
"higress-ai-search-mcp-server"
],
"env": {
"HIGRESS_URL": "http://localhost:8080/v1/chat/completions",
"MODEL": "qwen-turbo",
"INTERNAL_KNOWLEDGE_BASES": "Employee handbook, company policies, internal process documents"
}
}
}
}Tool list not available yet
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Fetch the live tool list by running this server in a temporary sandbox using the button above.
Higress AI-Search MCP Server is a Model Context Protocol (MCP) server that provides an AI search tool to enhance AI model responses with real‑time search results. It integrates with the Higress ai‑search feature to search various engines and internal knowledge bases.
Install via uvx (automatic install from PyPI) or clone the repository and use uv locally. Configure environment variables: HIGRESS_URL (optional, default http://localhost:8080/v1/chat/completions), MODEL (required), and INTERNAL_KNOWLEDGE_BASES (optional). Add the server configuration to your MCP client (e.g., Cline or Claude Desktop) with the appropriate command and args.
It provides an AI search tool that fetches results from external search engines and internal knowledge bases, then feeds them into an AI model to improve answer quality.
You need `uv` installed and a running Higress instance configured with both the `ai‑search` and `ai‑proxy` plugins.
Yes. The server connects to a Higress service at the URL specified by `HIGRESS_URL` (default `http://localhost:8080/v1/chat/completions`).
Google, Bing, Quark (general web search) and Arxiv (academic search). Internal knowledge base search is also supported.
Set environment variables `HIGRESS_URL`, `MODEL` (required), and optionally `INTERNAL_KNOWLEDGE_BASES`. Then add the server configuration to your MCP client.

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