Provides semantic search across local files by creating vector embeddings from watched directories.
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.
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:
~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json
~/Library/Application Support/Claude/claude_desktop_config.json
The server requires configuration through environment variables:
You must specify directories to watch using ONE of the following methods:
WATCH_DIRECTORIES
: Comma-separated list of directories to watchWATCH_CONFIG_FILE
: Path to a JSON configuration file with a watchList
arrayExample using WATCH_DIRECTORIES:
{
"mcpServers": {
"files-vectorstore": {
"command": "npx",
"args": [
"-y",
"@lishenxydlgzs/simple-files-vectorstore"
],
"env": {
"WATCH_DIRECTORIES": "/path/to/dir1,/path/to/dir2"
},
"disabled": false,
"autoApprove": []
}
}
}
Example using WATCH_CONFIG_FILE:
{
"mcpServers": {
"files-vectorstore": {
"command": "npx",
"args": [
"-y",
"@lishenxydlgzs/simple-files-vectorstore"
],
"env": {
"WATCH_CONFIG_FILE": "/path/to/watch-config.json"
},
"disabled": false,
"autoApprove": []
}
}
}
The watch config file should have the following structure:
{
"watchList": [
"/path/to/dir1",
"/path/to/dir2",
"/path/to/specific/file.txt"
]
}
CHUNK_SIZE
: Size of text chunks for processing (default: 1000)CHUNK_OVERLAP
: Overlap between chunks (default: 200)IGNORE_FILE
: Path to a .gitignore style file to exclude files/directories based on patternsExample with all optional parameters:
{
"mcpServers": {
"files-vectorstore": {
"command": "npx",
"args": [
"-y",
"@lishenxydlgzs/simple-files-vectorstore"
],
"env": {
"WATCH_DIRECTORIES": "/path/to/dir1,/path/to/dir2",
"CHUNK_SIZE": "2000",
"CHUNK_OVERLAP": "500",
"IGNORE_FILE": "/path/to/.gitignore"
},
"disabled": false,
"autoApprove": []
}
}
}
This server provides the following MCP tools:
Perform semantic search across indexed files.
Parameters:
query
(required): The search query stringlimit
(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
}
]
Get statistics about indexed files.
Parameters: None
Example response:
{
"totalDocuments": 42,
"watchedDirectories": ["/path/to/docs"],
"processingFiles": []
}
Query your local `mu` mail index for fast, structured mail search from MCP clients.
Provides real-time flight tracking and status information using the AviationStack API.
Extracts basic chemical information about drugs and compounds from the PubChem API.
Performs web searches using the Gemini Web Search Tool via the local gemini-cli.
An enhanced MCP server for SearXNG web searching, utilizing a category-aware web-search, web-scraping, and includes a date/time retrieval tool.
Query Shodan's database of internet-connected devices and vulnerabilities using the Shodan API.
Search for Google images, view results, and download them directly within your IDE.
Interact & query with Meilisearch (Full-text & semantic search API)
Search for messages and files within a Slack workspace using the Slack API.
Performs deep web searches for information using the Tavily API.