"VLC media player" matching MCP servers:

Enables natural-language search over locally indexed files such as markdown, text, images, videos, and PDFs, and retrieves indexed text or media metadata by path. It lets Cursor query a local embedding index built with Gemini and SQLite.

A nested MCP system that demonstrates server composition by using an orchestrator to manage an internal vector store for semantic search. It enables complex, multi-hop retrieval and reasoning over a knowledge base through an agentic reasoning loop.

Provides graph-based semantic memory storage and retrieval using vector embeddings and SQLite, enabling relationship creation between memories and similarity-based search through natural language.

A self-hostable remote MCP server that gives multiple AI agents shared, durable, user-owned memory with semantic search, versioned documents, reusable skills, and lessons. It keeps each account isolated while running on the user's own Cloudflare deployment.

Enables ingestion of text, files, URLs, and media sources into a local RAG pipeline, then semantic querying with verifiable citations including timestamps for audio and video. It exposes tools for ingesting, querying, listing documents, retrieving stats, and deleting documents via MCP.

Provides a local creator asset library MCP server that scans folders to catalog media files, batch-renames them, applies tags, tracks asset lineage between source and finished works, and offers keyword- and BGE-vector-based semantic search. It also lets other content-production MCP servers auto-register their generated outputs into the library for later retrieval and reuse.

Allows LLMs to access, scan, and search photos on connected iOS devices via USB using libimobiledevice and ChromaDB. It supports semantic search, metadata filtering, and automated file organization for efficient media management.

A fully offline local RAG server that utilizes ChromaDB and Ollama to index and query PDF, text, and Markdown documents. It allows users to manage local knowledge bases and perform semantic searches with AI-generated responses.

Auto-converts FastAPI endpoints into MCP tools for semantic search, data ingestion (text, code, conversations), and knowledge graph operations. Provides dual access through MCP protocol and direct API calls with automatic tool generation from FastAPI routes.