@lishenxydlgzs/simple-files-vectorstore

A Model Context Protocol (MCP) server that provides semantic search capabilities across files. This server watches specified directories and creates vector embeddings of file contents, enabling semantic search across your documents.

Installation & Usage

Add to your MCP settings file:

{
  "mcpServers": {
    "files-vectorstore": {
      "command": "npx",
      "args": [
        "-y",
        "@lishenxydlgzs/simple-files-vectorstore"
      ],
      "env": {
        "WATCH_DIRECTORIES": "/path/to/your/directories"
      },
      "disabled": false,
      "autoApprove": []
    }
  }
}

MCP settings file locations:

VSCode Cline Extension: ~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json
Claude Desktop App: ~/Library/Application Support/Claude/claude_desktop_config.json

Configuration

The server requires configuration through environment variables:

Required Environment Variables

WATCH_DIRECTORIES: Comma-separated list of directories to watch
{ "mcpServers": { "files-vectorstore": { "command": "npx", "args": [ "-y", "@lishenxydlgzs/simple-files-vectorstore" ], "env": { "WATCH_DIRECTORIES": "/path/to/dir1,/path/to/dir2" }, "disabled": false, "autoApprove": [] } } }

Optional Environment Variables

CHUNK_SIZE: Size of text chunks for processing (default: 1000)
CHUNK_OVERLAP: Overlap between chunks (default: 200)

MCP Tools

This server provides the following MCP tools:

1. search

Perform semantic search across indexed files.

Parameters:

query (required): The search query string
limit (optional): Maximum number of results to return (default: 5, max: 20)

Example response:

[
  {
    "content": "matched text content",
    "source": "/path/to/file",
    "fileType": "markdown",
    "score": 0.85
  }
]

2. get_stats

Get statistics about indexed files.

Parameters: None

Example response:

{
  "totalDocuments": 42,
  "watchedDirectories": ["/path/to/docs"],
  "processingFiles": []
}

Features

Real-time file watching and indexing
Semantic search using vector embeddings
Support for multiple file types
Configurable chunk size and overlap
Background processing of files
Automatic handling of file changes and deletions

Repository

GitHub Repository