higress ai search mcp server

Local 2025-08-31 23:23:13 0
search @cr7258/higress-ai-search-mcp-server

A Model Context Protocol server that enables AI models to perform real-time internet and knowledge searches through Higress, enhancing model responses with up-to-date information from Google, Bing, Arxiv, and internal knowledge bases.

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.

Higress AI-Search Server MCP server

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

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.

[
  {
    "description": "n    Enhance AI model responses with real-time search results from search engines.n    n    This tool sends a query to Higress, which integrates with various search engines to provide up-to-date information:n    n    🌐 **Internet Search**: Google, Bing, Quark - for general web informationn    📖 **Academic Search**: Arxiv - for scientific papers and researchn    👨‍💻 **Internal Knowledge Search**: Company policies, Product documentation, Technical specificationsn    n    Args:n        query: The user's question or search queryn        n    Returns:n        The enhanced AI response with search results incorporatedn    ",
    "inputSchema": {
      "properties": {
        "query": {
          "title": "Query",
          "type": "string"
        }
      },
      "required": [
        "query"
      ],
      "title": "ai_searchArguments",
      "type": "object"
    },
    "name": "ai_search"
  }
]