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Higress AI-Search MCP Server

by cr7258
GitHub
Python
Apache 2.0
5
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Higress AI-Search MCP 服务器

概述

模型上下文协议 (MCP) 服务器提供 AI 搜索工具，通过Higress ai-search功能利用来自各种搜索引擎的实时搜索结果增强 AI 模型响应。

演示

克莱恩

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

克劳德桌面

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

特征

  • 互联网搜索：Google、Bing、Quark - 用于一般网络信息
  • 学术搜索：Arxiv - 用于科学论文和研究
  • 内部知识搜索

先决条件

配置

可以使用环境变量来配置服务器：

  • HIGRESS_URL (可选)：Higress 服务的 URL（默认值： http://localhost:8080/v1/chat/completions ）。
  • MODEL （必需）：用于生成响应的 LLM 模型。
  • INTERNAL_KNOWLEDGE_BASES （可选）：内部知识库的描述。

选项 1：使用 uvx

使用 uvx 将自动从 PyPI 安装包，无需在本地克隆存储库。

{ "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" } } } }

选项 2：使用 uv 进行本地开发

使用 uv 需要在本地克隆存储库并指定源代码的路径。

{ "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" } } } }

执照

该项目根据 MIT 许可证获得许可 - 有关详细信息，请参阅LICENSE文件。

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A
security – no known vulnerabilities
A
license - permissive license
A
quality - confirmed to work

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

Tools

模型上下文协议服务器，使 AI 模型能够通过 Higress 执行实时互联网和知识搜索，并利用来自 Google、Bing、Arxiv 和内部知识库的最新信息增强模型响应。

  1. 概述
    1. 演示
      1. 克莱恩
      2. 克劳德桌面
    2. 特征
      1. 先决条件
        1. 配置
          1. 选项 1：使用 uvx
          2. 选项 2：使用 uv 进行本地开发
        2. 执照

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