"A YouTube MCP server with statistics, available via npx or Python command" matching MCP servers:

A lightweight MCP server for reading public YouTube data, offering tools to fetch video transcripts, playlist contents, and video metadata without requiring an API key.

Provides AI-native access to Swiss Federal Statistical Office datasets through 9 tools for querying education, population, and cross-cantonal comparisons without authentication.

MCP server for YouTubeTranscript.dev — extract transcripts, manage history, and power AI assistants with YouTube content.

A Model Context Protocol server that enables remote execution of shell commands across different operating systems, automatically handling platform-specific differences between Windows and Unix-like systems.

Enables Claude to query AirKorea's air pollution statistics, including real-time averages by province and city/county, as well as daily and monthly averages by monitoring station.

A proxy server that enables AI assistants to run and interact with command-line applications like Expo through the Model Context Protocol (MCP), capturing logs and allowing keypress forwarding.

A Python template for creating MCP servers with embedded documentation, featuring example weather service tools using the NWS API.

This server enables Claude to execute shell commands, read and edit files, and perform git operations on the host machine via a remote MCP endpoint.

A quickstart template to build and deploy a remote MCP server on Azure Functions using Python, secured with keys and HTTPS.

Provides comprehensive statistics and advanced analysis tools for the Korean stock market, offering real-time index data, sector analysis, investor trend tracking, and AI-based market pattern recognition.

Enables interactive communication with AI assistants by exposing custom tools through the Model Context Protocol, deployable on Render with optional bearer-token authentication.

A minimal MCP server template for Python with Streamable HTTP transport, bearer token authentication, and a hello tool, designed for deployment on Render.

Exposes public YouTube data — transcripts with timestamps and language listings, keyword search, video metadata and statistics, comments, channels, channel uploads, and categories — as read-only tools an LLM can call over stdio. It runs as a single local process using only a YouTube Data API key, with SQLite caching, quota tracking, and no OAuth or account access.

An MCP server that enables AI agents to pause and request human approval or information via Slack, Telegram, or macOS dialogs before proceeding with actions.

MCP server that provides YouTube video data to AI agents, supporting search, metadata, comments, and transcripts without an API key.

A production-grade MCP server providing a persistent Python REPL with multi-session support, sandboxing, and timeout protection, enabling LLM agents to execute Python code across multiple turns with variables that persist between calls.

A powerful MCP server for summarizing YouTube videos with transcript fetching, intelligent summarization, key point extraction, and metadata retrieval.

Enables YouTube integration with Claude Code, including video search, metadata retrieval, transcript fetching, channel exploration, and trending videos.

Enables AI assistants to access live YouTube data, including video search, transcripts, analytics, competitor research, SEO metadata, and creator monetization insights through the YouTube Data API and RSS feeds.

A Model Context Protocol server that allows LLMs to interact with Python environments, execute code, and manage files within a specified working directory.