Nse Bse MCP
The NSE-BSE MCP Server is a Model Context Protocol server that provides real-time stock market data for the National Stock Exchange of India and the Bombay Stock Exchange. It supports 66 tools for market data query, historical analysis, options derivatives, company information, and document download.
rating : 2.5 points
downloads : 3.3K
What is the NSE-BSE MCP Server?
This is an AI data server specifically designed for the Indian stock market. Through the Model Context Protocol (MCP), it allows AI assistants (such as Claude, ChatGPT, Gemini, etc.) to access and analyze real-time market data from India's two major stock exchanges (NSE and BSE). It offers 66 different data tools covering various aspects, including real-time quotes, historical data, company information, and IPO details.How to use the NSE-BSE MCP Server?
You can start the server via a simple command line and then configure the connection in your preferred AI assistant application. After the server is started, the AI assistant can directly query Indian stock market data, such as obtaining stock prices, viewing market trends, and analyzing company financial reports.Use cases
Suitable for investors, analysts, researchers, and anyone who needs to understand information about the Indian stock market. You can ask the AI assistant to: monitor your investment portfolio, research company fundamentals, analyze market trends, obtain IPO information, view company announcements, etc.Main features
Comprehensive market data coverage
Provides 66 data tools covering all major functions of the NSE (44) and BSE (20), including real-time quotes, historical data, option chains, corporate actions, etc.
Intelligent response limitation
Automatically processes large data sets and returns metadata for the AI to decide which specific information to obtain, avoiding response overload.
Document download and processing
Supports downloading and analyzing documents such as IPO prospectuses, company annual reports, and announcements. The AI can directly read the content of the documents.
Multiple deployment methods
Supports direct running via npm, running from source code, and Docker containerized deployment to meet the needs of different users.
Compatibility with mainstream AI assistants
Supports mainstream AI assistant platforms such as Claude Desktop, ChatGPT, and Gemini CLI.
Ready for production environment
Includes production-level features such as health checks, CORS support, and HTTP stream transmission.
Advantages
Obtain data from India's two major exchanges in one stop without switching between multiple platforms
The AI assistant can directly analyze the data and provide investment advice and market insights
Real-time data updates ensure the timeliness of information
Supports complex queries and data analysis, going beyond simple data viewing
Open source and free, allowing self-deployment and customization
Good error handling and fault tolerance mechanisms
Limitations
Requires basic command-line operation knowledge for deployment
Relies on third-party APIs, and data availability is affected by the source APIs
Requires configuration of the AI assistant client for use
May have a certain learning curve for users with no technical knowledge
Some advanced features may require network proxy settings
How to use
Install and start the server
Choose a suitable way to start the MCP server
Configure the AI assistant client
Add the MCP server configuration to the AI assistant application you are using
Start using
Restart the AI assistant application. Now you can ask questions related to the Indian stock market
Usage examples
Stock research and analysis
Ask the AI assistant to research the fundamental and technical aspects of a stock
Market monitoring and early warning
Monitor the performance of specific stocks or the entire market
IPO investment decision
Research upcoming or recently listed IPOs
Investment portfolio management
Track and manage your investment portfolio
Frequently Asked Questions
Do I need programming knowledge to use this server?
Is this service free?
Is the data real-time? What's the latency?
Which AI assistants are supported?
Do I need an Indian mobile phone number or account?
Can the server be deployed in the cloud?
Does the data include historical data? How far back can it go?
What should I do if the server has problems?
Related resources
GitHub repository
Project source code and latest updates
Model Context Protocol official documentation
Technical documentation and specifications of the MCP protocol
Bun installation guide
Installation and usage guide for the Bun JavaScript runtime
Docker installation guide
Installation and usage guide for the Docker container platform
NSE National Stock Exchange of India
Official website of the National Stock Exchange of India
BSE Bombay Stock Exchange
Official website of the Bombay Stock Exchange

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