Integrations
Processes and returns OI-Wiki content in Markdown format, allowing AI to reference competitive programming documentation and algorithms directly
Utilizes Milvus Lite as a vector database to store and retrieve semantic vectors of OI-Wiki content, enabling semantic search capabilities for competitive programming knowledge
mcp-oi-wiki
让大模型拥有 OI-Wiki 的加成!
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:
然后打开你的 MCP 配置文件(mcpo 或 claude):
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:
在批量推理页面下载摘要结果到 result.jsonl
。
最后运行:
生成新的 db/oi-wiki.db
。
Thanks
You must be authenticated.
Tools
Enhances large language models with competitive programming knowledge by leveraging OI-Wiki content through vector search, allowing models to retrieve relevant algorithms and techniques.
Related MCP Servers
- -securityFlicense-qualityEnables AI assistants to enhance their responses with relevant documentation through a semantic vector search, offering tools for managing and processing documentation efficiently.Last updated -6213TypeScript
- -securityAlicense-qualityProvides RAG capabilities for semantic document search using Qdrant vector database and Ollama/OpenAI embeddings, allowing users to add, search, list, and delete documentation with metadata support.Last updated -54TypeScriptApache 2.0
- -securityFlicense-qualityA smart code retrieval tool based on Model Context Protocol that provides efficient and accurate code repository search capabilities for large language models.Last updated -Python
- -securityAlicense-qualityProvides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context.Last updated -62TypeScriptMIT License