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Search a personal document collection semantically and retrieve full source documents.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Personal Knowledge-Base MCP Server" yet — see the docs or source repo.
Please semantically search my knowledge base for "explanations of eigenvalues in linear algebra" and return the most relevant note snippets with their sources.
Returns several relevant note snippets and identifies the source document for each.
Based on the previous search results, open the most relevant document and return its full content.
Outputs the full text of the selected document for further reading or summarization.
Please list all source documents currently indexed in the knowledge base.
Returns a list of document sources currently indexed.
Students can semantically search their own notes and study materials without remembering exact filenames or keywords. After finding a result, they can open the full document to review the full context.
Researchers can look up concepts, findings, or prior notes across a personal document collection. The tool also supports opening the original matching documents and listing indexed sources.
Writers can search their past materials, excerpts, and ideas before drafting to quickly locate relevant content. This reduces the time spent manually browsing files.
It is a personal knowledge-base MCP server for semantic search over a student-owned document collection. It also provides tools to retrieve full documents and list indexed sources.
The provided description says it is built with MCP, Gemini embeddings, and Qdrant. More detailed runtime and configuration information is not provided.
Its known capabilities include searching notes, retrieving full documents, and listing indexed sources. For anything beyond that, see the source repository.
Search and retrieve knowledge base documents with Qdrant hybrid retrieval.
Search local documents by keyword, fetch passages, and list sources offline.
Search and retrieve local documents semantically for faster AI-powered knowledge access.
Search markdown knowledge bases with hybrid ranking and intelligent reranking.
Turn local notes into a private searchable knowledge base for AI assistants.
Index PDFs into Qdrant and enable semantic search and RAG document QA.