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.
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 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.
MCP server adapter that exposes A-share stock data tools, prompts, and resources via FastMCP, enabling querying of stocks, K-lines, financials, sectors, and market hot spots through natural language.
Enables AI clients to analyze any company domain and determine its AI maturity tier (commercialized, deployed, declared, or none) with supporting evidence, via a single tool backed by an Apify actor.
Academic peer-review (HAKEM), research-gap finding, journal recommender (1,214 venues with predatory flags), duplicate publication checker, and article writer tools from Science AI Journal. Free local FTS5 tools + LLM-backed tools that bill the caller's account.
Enables coding agents to query AI model API prices, including historical point-in-time lookups with cited sources, using a bundled dated dataset and requiring no API keys.
Enables AI agents to query LLM and multimodal model benchmarks, pricing, speed, and track model updates via structured diffs using the Artificial Analysis public API.
Local-first MCP server for Originality.ai workflows, including AI detection, plagiarism checks, readability, SEO scans, and scan-result retrieval for content teams.
Multi-AI Consensus Tool: Query multiple AI models in parallel, synthesize responses for better accuracy, and reduce AI bias through ensemble decision-making.