
daltonnyx/userful-mcps
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A collection of standalone Python scripts that implement Model Context Protocol (MCP) servers for various utility functions.
Обзор
A collection of standalone Python scripts that implement Model Context Protocol (MCP) servers for various utility functions. Each server provides specialized tools that can be used by AI assistants or other applications that support the MCP protocol. The Model Context Protocol (MCP) is a standardized way for AI assistants to interact with external tools and services. It allows AI models to extend their capabilities by calling specialized functions provided by MCP servers. Communication happens via standard input/output (stdio) using JSON messages. Each MCP server is designed to be run using a Python environment manager like uv. A server that extracts information from YouTube videos using yt-dlp. - : Get chapter information from a YouTube video. - : Get subtitles from a YouTube video for specific chapters or the entire video. A server for manipulating Word documents, including template processing and PDF conversion.
README
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Useful Model Context Protocol Servers (MCPS)
A collection of standalone Python scripts that implement Model Context Protocol (MCP) servers for various utility functions. Each server provides specialized tools that can be used by AI assistants or other applications that support the MCP protocol.
What is MCP?
The Model Context Protocol (MCP) is a standardized way for AI assistants to interact with external tools and services. It allows AI models to extend their capabilities by calling specialized functions provided by MCP servers. Communication happens via standard input/output (stdio) using JSON messages.
Available Servers
Each MCP server is designed to be run using a Python environment manager like
uv.
YouTube Data Extractor (ytdlp)
A server that extracts information from YouTube videos using yt-dlp.
Tools:
- Extract Chapters: Get chapter information from a YouTube video.
- Extract Subtitles: Get subtitles from a YouTube video for specific chapters or the entire video.
MCP Server Configuration:
"mcpServers": {
"ytdlp": {
"name": "youtube", // Optional friendly name for the client
"command": "uv",
"args": [
"run",
"--directory", "/useful-mcps/ytdlp", // Path to the MCP directory containing pyproject.toml
"--", // Separator before script arguments, if any
"ytdlp_mcp" // Match the script name defined in pyproject.toml [project.scripts]
]
// 'cwd' is not needed when using --directory
}
}
Word Document Processor (docx_replace)
A server for manipulating Word documents, including template processing and PDF conversion.
Tools:
- Process Template: Replace placeholders in Word templates and manage content blocks.
- Get Template Keys: Extract all replacement keys from a Word document template.
- Convert to PDF: Convert a Word document (docx) to PDF format.
MCP Server Configuration:
"mcpServers": {
"docx_replace": {
"name": "docx", // Optional friendly name
"command": "uv",
"args": [
"run",
"--directory", "/useful-mcps/docx_replace", // Path to the MCP directory
"--",
"docx_replace_mcp" // Match the script name defined in pyproject.toml
]
}
}
PlantUML Renderer (plantuml)
A server for rendering PlantUML diagrams using a PlantUML server (often run via Docker).
Tools:
- Render Diagram: Convert PlantUML text to diagram images (e.g., PNG).
MCP Server Configuration:
"mcpServers": {
"plantuml": {
"name": "plantuml", // Optional friendly name
"command": "uv",
"args": [
"run",
"--directory", "/useful-mcps/plantuml", // Path to the MCP directory
"--",
"plantuml_server" // Match the script name defined in pyproject.toml
]
Установка
This server does not publish a one-line install command.
Open the repository installation guide Новичок в MCP? Начните с руководства на mcpskill.org →Конфигурация
"mcpServers": {
"ytdlp": {
"name": "youtube", // Optional friendly name for the client
"command": "uv",
"args": [
"run",
"--directory", "<path/to/repo>/useful-mcps/ytdlp", // Path to the MCP directory containing pyproject.toml
"--", // Separator before script arguments, if any
"ytdlp_mcp" // Match the script name defined in pyproject.toml [project.scripts]
]
// 'cwd' is not needed when using --directory
}
}