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    Higress Ai Search Mcp Server

    An MCP server enhances AI responses with real-time search results via Higress ai-search.

    5 stars
    Python
    Updated Aug 25, 2025

    Table of Contents

    • Overview
    • Demo
    • Cline
    • Claude Desktop
    • Features
    • Prerequisites
    • Configuration
    • Option 1: Using uvx
    • Option 2: Using uv with local development
    • License

    Table of Contents

    • Overview
    • Demo
    • Cline
    • Claude Desktop
    • Features
    • Prerequisites
    • Configuration
    • Option 1: Using uvx
    • Option 2: Using uv with local development
    • License

    Documentation

    MseeP.ai Security Assessment Badge

    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.

    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.

    bash
    {
      "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.

    bash
    {
      "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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