"A guide for managing personal files" matching MCP servers:

Enables LibreChat agents to manage per-user private files, persistent documentation, RAG indexing and semantic search, and publish files via secure opaque public links.

Improves AI agent task performance by providing task area segmentation, hierarchical RAG, and hybrid search capabilities.

A personal AI memory service based on MCP protocol that provides long-term memory capabilities for various AI clients.

Enables querying, listing, and summarizing personal knowledge base documents using RAG with hybrid search and LLM.

Provides semantic search capabilities over the Plesk Extensions Guide documentation using Retrieval-Augmented Generation (RAG) and vector embeddings. It enables AI assistants to retrieve relevant technical information and answer natural language queries regarding Plesk extension development.

Enables AI agents to answer questions about a personal site straight from its published JSON bundle — profile, posts, case studies, pages, projects, stats and small datasets — through seven read-only tools for listing, full-text search, fetching Markdown, and querying dataset rows, with no sign-in, database or write path.

A guide for implementing Model Context Protocol (MCP) servers that provide AI models with external tools like web search, text manipulation, and mathematical operations.

Enables MCP-compatible AI clients to securely access a user's personal context by exposing connector data, starting with recent Spotify listening activity, through per-user OAuth and tools.

A privacy-first memory layer for AI that securely bridges local knowledge with AI assistants through MCP tools, with intelligent redaction and local vector database.

Exposes a personalized AI agent that reads your resume and provides intelligent responses about your professional background through a standardized MCP server interface with RAG capabilities.

Provides AI assistants with persistent, graph-based memory using Neo4j, enabling semantic search and complex relationship tracking. It features specialized Cloudflare Access support for secure remote connections and isolated multi-database management for different projects.

Enables MCP clients to search encrypted, self-hosted archives and retrieve bounded records from Apple, Canvas, Health, travel, and Obsidian sources while checking sync freshness.

MCP server providing weather lookup, semantic search over personal notes (RAG), and image generation tools for any MCP client like Claude Desktop.

Enables natural-language management of calendar events, notes, and scanned or photographed documents through a ReAct agent that schedules and reschedules events, detects scheduling conflicts, and searches notes with hybrid vector plus keyword retrieval. It also ingests visual documents via an OCR/CNN vision worker, stores long-term agent facts, and synthesizes cross-context summaries.

Provides AI-assisted long-term memory storage and retrieval with exact-phrase and semantic hybrid search, enabling save, read, delete, and admin recovery via MCP tools.

Indexes local and enterprise documents to provide a unified personal knowledge base for AI clients via the Model Context Protocol. It supports full-text search across various file formats and integrates with platforms like Feishu and WeChat Work.

A semantic-memory MCP server that stores text 'memories' with provenance and enables recall by meaning (vector search), keyword (FTS5), or structured filters.

MCP server that indexes your Obsidian notes into a Milvus vector database and enables querying them via a local or OpenAI LLM, with real-time synchronization.

Personal local AI memory/document MCP that manages short and long-term memories and Markdown documents, with tools for import, search, and retrieval.

A local-first RAG system that indexes personal documents and enables querying them via an MCP tool, keeping data private with local embeddings.