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"How to get the file tree structure of a folder" matching MCP servers:

  • Home File Agent

    nfedunwork-code
    F
    license
    -
    quality
    C
    maintenance
    MCP server that provides secure read-only access to a local folder, enabling file listing, reading, semantic search (RAG), and indexing status via natural language, integrated with Claude Desktop and a custom agent loop.

  • THE RAG MCP

    Sankalp-2005
    F
    license
    -
    quality
    C
    maintenance
    An enterprise-ready MCP server that exposes a RAG tool for retrieving relevant context and metadata from a Qdrant vector database using natural language queries.
    2

  • Tiny Chat

    to-aoki
    A
    license
    D
    quality
    C
    maintenance
    A lightweight RAG system that provides an MCP server for searching and interacting with vector-based knowledge bases. It enables users to perform retrieval-augmented generation and search across Qdrant collections through a standardized interface.
    1
    2
    MIT

  • rag_mcp

    mmer547
    F
    license
    -
    quality
    C
    maintenance
    Enables retrieval-augmented generation by allowing LLMs to search documents in a local folder using vector similarity, supporting multiple file formats.
  • Tribal by tribal-memory

    Tribalofficial

    tribal-memory
    F
    license
    A
    quality
    A
    maintenance
    Semantic memory for AI builders: capture the tacit engineering know-how that never reaches your docs, recall it the moment it applies. Built in Rust on Postgres and pgvector.
    10
    9

  • semantic-code-mcp

    vrppaul
    F
    license
    A
    quality
    C
    maintenance
    A local MCP server that provides semantic code search for Python codebases using tree-sitter for chunking and LanceDB for vector storage. It enables natural language queries to find relevant code snippets based on meaning rather than just text matching.
    3
    3

  • MCP-Markdown-RAG

    Zackriya-Solutions
    A
    license
    A
    quality
    D
    maintenance
    A Model Context Protocol (MCP) server that provides a local-first RAG engine for your markdown documents. It uses a file-based Milvus vector database to index your notes, enabling LLMs to perform semantic search and retrieve relevant content from your local files.
    3
    55
    Apache 2.0
  • ArcadeDB Multi-Model DBMS by ArcadeData

    ArcadeDB Multi-Model DBMSofficial

    ArcadeData
    A
    license
    A
    quality
    A
    maintenance
    ArcadeDB Multi-Model Database, one DBMS that supports SQL, Cypher, Gremlin, HTTP/JSON, MongoDB and Redis. ArcadeDB is a conceptual fork of OrientDB, the first Multi-Model DBMS. ArcadeDB supports Vector Embeddings.
    10
    1,080
    Apache 2.0

  • MCP Tooling Lab

    kaypon
    F
    license
    B
    quality
    D
    maintenance
    A Node.js-based MCP server that enables AI agents to generate embeddings, index documents, and perform semantic vector searches using OpenAI and Chroma. It facilitates the creation of retrieval-augmented generation (RAG) pipelines for internal knowledge assistants and document-based workflows.
    3

  • MCP Router

    Maverick-LjXuan
    F
    license
    B
    quality
    D
    maintenance
    A service discovery and proxy for MCP servers that enables registration, discovery, and execution of tools on remote MCP servers. Uses vector-based similarity search through Alibaba Cloud services to intelligently route requests to appropriate MCP services.
    3
  • LanceDB MCP Server by lancedb

    LanceDB MCP Serverofficial

    lancedb
    F
    license
    B
    quality
    D
    maintenance
    A basic serverless MCP server using LanceDB to store and retrieve documents via three tools: ingest, retrieve, and get table details.
    3
    25
  • Memgraph MCP Server by memgraph

    Memgraph MCP Serverofficial

    memgraph
    -
    license
    C
    quality
    -
    maintenance
    A lightweight server implementation of the Model Context Protocol that connects Memgraph database with LLMs, allowing users to interact with graph databases through natural language.
    1
    25