Enables researching YouTube channels and videos by listing uploads, reading transcripts, extracting frames, and searching, without needing a YouTube API key.
Real human judgment as agent tools -- an AI agent can ask a question and get back a structured, schema-validated JSON answer from a real quality-scored human. 16 response types (yes/no, ratings, rankings, A/B tests, sentiment, image/video/audio review, voice/video/photo capture). Fully programmatic signup with a $5 free trial credit, no card required.
A hosted Model Context Protocol server providing read-only YouTube tools for search, video/channel data, and transcripts, with no Google Cloud project or API key required.
MCP server for extracting structured intelligence from YouTube channels and videos — transcripts, topics, and competitive signals for AI-powered research workflows.
Enables AI assistants to access YouTube organic analytics, including channel stats, video performance, watch time, and audience engagement, via the YouTube Data API v3 and Analytics API v2.
Minimalistic MCP server that lets AI assistants inspect, quality-check, and clean CSV datasets through tools, resources, and prompts, without needing local file access.
MCP server providing 29 A-share analysis skills including real-time data, capital flow, limit-up tracking, technical/fundamental analysis, backtesting, risk control, and Xueqiu portfolio tracking, enabling AI agents to execute market research and strategy tasks.
Provides MCP tools for fetching timestamped YouTube transcripts and top comments, scanning spreadsheets for video links, and a local web UI for grounded video summaries.
This MCP server enables users to search for scientific papers on arXiv and retrieve detailed metadata for specific papers. It provides tools to perform search queries and fetch in-depth information using paper IDs.
Provides comprehensive A-share (Chinese stock market) data including stock information, historical prices, financial reports, macroeconomic indicators, technical analysis, and valuation metrics through the free Baostock data source.
Enables simulation and analysis of M/M/1 and M/M/c queuing systems using SimPy, with tools for parameter validation, theoretical metric calculation, simulation execution, and comparison of separate vs pooled queue strategies.