"deepseek" matching MCP servers:

Helps developers tackle legacy codebases by giving AI coding assistants context through Qdrant vector store and Agentic RAG with Ollama or DeepSeek.

Exposes a layered long-term memory store — persistent self blocks, four-tier scoped retrieval, knowledge graph, and signed knowledge capsules — over stdio so any MCP-capable client can use the same 15 memory tools and shared ACL. It lets Claude Desktop, IDE agents, and custom orchestrators mount that store without depending on the DeepSeek Harness runtime.

A RAG MCP server that enables retrieval-augmented question answering over PyTorch documentation, with hybrid search (FAISS+Chroma, BM25) and source-cited responses from DeepSeek.