What types of financial data does CnStock offer?

It provides basic stock information, real-time quotes, historical K-lines, financial statements, and real-time calculated technical indicators like KDJ, MACD, RSI, and Bollinger Bands. Data is available in brief, medium, or full detail.

CnStock is a Model Context Protocol (MCP) service designed for large language models (LLMs), providing comprehensive A-share stock and in-market ETF data.

How does CnStock source its data?

CnStock uniquely utilizes reliable open-source data sources such as AkShare and efinance, completely removing any dependency on private APIs and ensuring data stability and accessibility.

Can I integrate CnStock with my existing LLM applications?

Yes, CnStock is designed for easy integration with popular MCP clients like Claude Desktop, CherryStudio, and DeepChat. You can simply configure the service URL to connect.

CnStock

Name: CnStock
Author: lllyin

bylllyin

0•

Data Science & ML

Web Scraping & Data Collection

API Development

Provides A-share stock data and in-market ETF quotes as a Model Context Protocol (MCP) service for large language models.

CnStock offers a comprehensive Model Context Protocol (MCP) service specifically designed to provide A-share stock data and in-market ETF quotes for large language models. Built upon robust open-source data sources like AkShare and efinance, it eliminates reliance on private APIs. The service delivers detailed financial metrics, real-time market data, and optimized technical indicators, ensuring data accuracy aligned with mainstream trading applications, and supports tiered data access tailored for different information needs.

Key Features

01Covers comprehensive market data, including basic information, real-time quotes, historical K-lines, and financial statements.

02Provides real-time calculation of technical indicators like KDJ, MACD, RSI, and Bollinger Bands with optimized algorithms for accuracy.

030 GitHub stars

04Utilizes open-source data sources (AkShare, efinance) for A-share and in-market ETF data, removing private API dependency.

05Supports `.env` environment configuration for enhancing data source stability and proxy settings.

06Offers tiered data access (brief, medium, full) to provide varying levels of detail for query results.

Use Cases

01Accessing real-time and historical stock market data through popular MCP clients such as Claude Desktop, CherryStudio, or DeepChat.

02Interactive debugging and testing of stock data queries using MCP Inspector.

03Integrating comprehensive A-share stock and in-market ETF data into large language models (LLMs) via the MCP service.