What search engines are supported?
Google, Bing, and Quark for internet search; Arxiv for academic search; plus configurable internal knowledge bases.
Higress AI-Search MCP Server
@MCP-Mirror
Basic information
About Higress AI-Search MCP Server
Mirror of
Higress AI-Search MCP Server config
No standard config provided
This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.
RepositoryHigress AI-Search MCP Server tools
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Overview
What is Higress AI-Search MCP Server?
The Higress AI-Search MCP Server is a Model Context Protocol (MCP) server that provides an AI search tool. It enhances AI model responses with real‑time search results from multiple search engines through the Higress ai‑search feature. This server is for developers and users who want to give AI assistants access to live web, academic, and internal knowledge data.
How to use Higress AI-Search MCP Server?
Install via uvx (automatic from PyPI) or uv with a local clone. Configure the server by setting environment variables – MODEL (required) and optionally HIGRESS_URL (default http://localhost:8080/v1/chat/completions) and INTERNAL_KNOWLEDGE_BASES. Add the server configuration to your MCP client (e.g., Claude Desktop or Cline).
Key features of Higress AI-Search MCP Server
- Internet search via Google, Bing, and Quark
- Academic search via Arxiv
- Internal knowledge base search
- Real‑time search result integration into AI responses
- Configurable LLM model and Higress endpoint
Use cases of Higress AI-Search MCP Server
- Enhance chatbot answers with up‑to‑date web information
- Retrieve scientific papers and research from Arxiv
- Search internal company documents (employee handbook, policies)
Frequently asked questions
What environment variables are needed?
`MODEL` is required. `HIGRESS_URL` is optional (defaults to `http://localhost:8080/v1/chat/completions`). `INTERNAL_KNOWLEDGE_BASES` is optional for describing your internal knowledge sources.
How do I install the server?
You can use `uvx` to install automatically from PyPI, or clone the repository and run with `uv` pointing to the local source.
What are the prerequisites?
You need `uv` for package management and a Higress gateway configured with the ai‑search and ai‑proxy plugins.
Who should use this server?
Anyone who wants to give MCP‑compatible AI assistants (like those in Claude Desktop or Cline) the ability to perform live searches across the web, academic sources, or internal knowledge bases.
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