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"How to search files on a local computer" matching MCP servers:

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    A very simple vector store that provides capability to watch a list of directories, and automatically index all the markdown, html and text files in the directory to a vector store to enhance context.
    15
    42
    MIT
  • A
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    Privacy-first local document search using semantic search. Runs entirely on your machine with no cloud services, supporting PDF, DOCX, TXT, and Markdown files.
    9
    3,271
    365
    MIT
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    Enables AI agents to search local Markdown documents using natural language, with automatic indexing and section-level retrieval.
    9
    2
    1
    MIT
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    Enables storing and retrieving text passages based on semantic meaning using local embeddings (Ollama) and vector storage (ChromaDB), allowing conversational memorization and retrieval of information.
    5
    18
    MIT
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    Semantic, on-demand skill retrieval for Claude Code that saves tokens and improves skill discovery by replacing the native skill listing with vector embedding search.
    8
    MIT
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    Local offline semantic search over documents (txt, md, pdf, docx, pptx, csv). Indexes folders into a LanceDB vector database with multilingual embeddings and supports hybrid vector + keyword search via Reciprocal Rank Fusion. No API keys, no cloud, no Docker required.
    28
    AGPL 3.0
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    A fully local, self-hosted memory server for MCP clients (Claude Code, Cursor, etc.) that provides persistent memory storage with semantic search, using local embeddings and a local Qdrant vector store.
    MIT
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    An MCP server that enables hybrid semantic and keyword retrieval over your documents, using PostgreSQL and pgvector as the backend. It fuses rankings from both methods to provide high-quality search results to the language model.
    MIT
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    A Docker-based local RAG backend that provides advanced document search capabilities using vector, graph, and full-text retrieval via the Model Context Protocol. It supports over 28 file formats and tracks evolving relationships between concepts using a Neo4j-backed graphiti implementation.
    1
    MIT
  • F
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    A local-first MCP server that enables semantic search over PDF and DOCX documents using structure-aware parsing and vector storage. It allows users to query their local knowledge base through Claude Code without cloud dependencies or GPU requirements.