A-Share Data: Real-Time Stock Analysis & Market Insights

Unlock In-Depth Insights with A-Share Data: Real-Time Stock Analysis & Market Insights

Supercharge your AI-powered financial solutions with A-Share Data. Designed exclusively for developers and teams utilizing Claude Code, Cursor, and Codex, this AI agent skill delivers comprehensive China A-shares market analysis. Seamlessly access real-time stock quotations, deep dive into historical data, and leverage advanced technical indicators to inform your strategic investment decisions.

What This Skill Does

A-Share Data provides an all-encompassing toolkit to explore the wealth of China's stock market data. Here's what you can accomplish:

• Receive real-time market updates that include index movements, price changes, and the latest market activities.
• Analyze historical financial data and performance reports to gauge the track record of specific stocks or industry sectors.
• Utilize technical indicators for a thorough technical analysis of stocks, aiding in spotting potential trends and reversals.
• Stay informed on major company events impacting dual-listed A+H stocks, including key IPO stages in Hong Kong.
• Identify and track hot industries and concepts, as well as monitor sector performance, visualized through a heat map.
• Access a curated list of 7x24 market news to stay ahead in the fast-paced world of stock trading.

Use Cases

Transform your AI applications with this robust skill. Possible scenarios include:

• Empowering AI-driven stock trading bots to make informed decisions using real-time data and technical analysis.
• Developing market analysis dashboards for financial analysts seeking in-depth, structured insights into the A-share market.
• Creating news aggregation apps that filter and prioritize market updates relevant to specific stocks or sectors.

Technical Details

• Languages and Tools: Python scripts utilizing libraries like Akshare, MyTT, Pandas, Numpy, and Requests.
• Script Capabilities: Real-time data fetching, historical data analysis, technical analysis, stock event tracking, and sector information retrieval.
• File Paths and Environment: Scripts executed from specified SKILL_DIR paths using command line parameters.
• APIs and Data Sources: Integrations with repositories such as fetch_realtime.py, fetch_history.py, and fetch_danginvest.py for reliable data acquisition.

Capitalize on A-Share Data to redefine how your AI applications interact with the stock market landscape, providing actionable insights and maintaining a competitive edge.

Source & Licence

This package is built on open-source work published by shouldnotappearcalm (shouldnotappearcalm/a-share-skill) and distributed under MIT. The original licence text and copyright notice are included in your download.

Personal and commercial use, modification and redistribution are permitted, provided the original copyright and licence notice are retained.

Your purchase covers curation, licence verification, packaging, documentation and instant delivery. It does not grant exclusive rights to the underlying open-source code, which remains available under its original licence.

Delivery & Support

• Delivery: instant — a secure download link is emailed to you as soon as payment is confirmed.
• Format: ZIP archive containing the skill files, documentation and the original licence.
• Support: support@mcpcart.com — we aim to reply within 2 business days.
• Updates: updates are included only where stated on this page.

Refunds

This is a digital product delivered immediately after purchase. By completing your order you request immediate delivery and acknowledge that, once the download has been accessed, the statutory right to cancel no longer applies to the extent permitted by law. Refund requests are handled in accordance with our published Refund Policy.

Claude, Codex, Gemini and Cursor are trademarks of their respective owners. MCP Cart is an independent marketplace and is not affiliated with, endorsed by, or sponsored by any of them. Compatibility references describe interoperability only.