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MCP Server

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.

22
GitHub Stars
11/23/2025
Last Updated
MCP Server Configuration
1{
2 "name": "oi-wiki",
3 "command": "uv",
4 "args": [
5 "--directory",
6 "/mcp-oi-wiki",
7 "run",
8 "python",
9 "main.py"
10 ]
11}
JSON11 lines
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README Documentation

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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

  • milvus-io/milvus-lite: A lightweight version of Milvus 向量数据库
  • OI-wiki/OI-wiki: :star2: Wiki of OI / ICPC for everyone. (某大型游戏线上攻略,内含炫酷算术魔法) OI-wiki
  • qdrant/fastembed: Fast, Accurate, Lightweight Python library to make State of the Art Embedding CPU 向量嵌入

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Model Context Protocol
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