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by andrea9293 • Uncategorized
A TypeScript MCP server for local-first document management and semantic search with embedded vector database and AI-powered capabilities.
Local-first document storage and management without relying on external databases.
Hybrid semantic search combining full-text and vector similarity across documents.
AI-powered contextual document analysis and search using Google Gemini.
This MCP server provides a local-first solution for managing documents with semantic search powered by an embedded Orama vector database. It supports hybrid search combining full-text and vector similarity, intelligent chunking of documents, and optional AI-enhanced search using Google Gemini. The built-in web UI offers a comprehensive dashboard for document management, search, and file uploads without requiring external databases or cloud services.
Add a new document to the knowledge base
Delete a document from the collection
Search for chunks within a specific document using semantic similarity. Always tell the user if result is truncated because of length. for example if you recive a message like this in the response: 'Tool response was too long and was truncated'
Use this tool only when user explicitly requests it. Retrieve a specific document by ID. Always tell the user if result is truncated because of length. for example if you recive a message like this in the response: 'Tool response was too long and was truncated'
List all documents in the knowledge base
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