Higress AI-Search MCP Server

by MCP-Mirror

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About

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…

Details

Author
MCP-Mirror
Downloads
306
Categories
Search

- 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

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).

Higress AI-Search MCP Server

Overview

A Model Context Protocol (MCP) server that provides an AI search tool to enhance AI model responses with real-time search results from various search engines through Higress ai-search feature.

<a href="https://glama.ai/mcp/servers/gk0xde4wbp">
Higress AI-Search Server MCP server
</a>

Demo

Cline

https://github.com/user-attachments/assets/60a06d99-a46c-40fc-b156-793e395542bb

Claude Desktop

https://github.com/user-attachments/assets/5c9e639f-c21c-4738-ad71-1a88cc0bcb46

Features

- Internet Search: Google, Bing, Quark - for general web information
- Academic Search: Arxiv - for scientific papers and research
- Internal Knowledge Search

Prerequisites

- uv for package installation.
- Config Higress with ai-search plugin and ai-proxy plugin.

Configuration

The server can be configured using environment variables:

- HIGRESS_URL(optional): URL for the Higress service (default: http://localhost:8080/v1/chat/completions).
- MODEL(required): LLM model to use for generating responses.
- INTERNAL_KNOWLEDGE_BASES(optional): Description of internal knowledge bases.

Option 1: Using uvx

Using uvx will automatically install the package from PyPI, no need to clone the repository locally.

{
  "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"
      }
    }
  }
}

Option 2: Using uv with local development

Using uv requires cloning the repository locally and specifying the path to the source code.

{
  "mcpServers": {
    "higress-ai-search-mcp-server": {
      "command": "uv",
      "args": [
        "--directory",
        "path/to/src/higress-ai-search-mcp-server",
        "run",
        "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"
      }
    }
  }
}

License

This project is licensed under the MIT License - see the LICENSE file for details.

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