MCP Servers

MCP OI-Wiki

Enhances large language models with competitive programming knowledge by leveraging OI-Wiki content through vector search, allowing models to retrieve relevant algorithms and techniques.

Tools

OI Wiki 致力于成为一个免费开放且持续更新的编程竞赛知识整合站点，大家可以在这里获取与竞赛相关的、有趣又实用的知识。本工具能够在 OI-wiki 中搜索相关的知识点。 query 应该比较详细，与要实现的算法/目标相关。比如：“求一个图的最小生成树”，“维护区间加/区间求和” @ param query 描述要实现的需求

README

mcp-oi-wiki

让大模型拥有 OI-Wiki 的加成！

乘法逆元搜索结果

How does it work?

使用 Deepseek-V3 对 OI-wiki 当前的 462 个页面做摘要，将摘要嵌入为语义向量，建立向量数据库。

查询时，找到数据库中最接近的向量，返回对应的 wiki markdown。

Usage

确保你拥有 uv。

首先，下载本仓库：

cd <path of MCP servers>
git clone --recurse-submodules https://github.com/ShwStone/mcp-oi-wiki.git

然后打开你的 MCP 配置文件（mcpo 或 claude）：

{
  "mcpServers": {
    "oi-wiki": {
      "command": "uv",
      "args": [
        "--directory",
        "<path of MCP servers>/mcp-oi-wiki",
        "run",
        "python",
        "main.py"
      ]
    }
  }
}

Update

可以生成自己的 db/oi-wiki.db。

将 Silicon flow API key 放在 api.key 文件中。

然后运行：

uv run script/request.py

在批量推理页面下载摘要结果到 result.jsonl。

最后运行：

uv run script/gendb.py

生成新的 db/oi-wiki.db。

Thanks

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