Read-only tools for analyzing Nifty 500 Indian stocks across daily, 15-minute, and 5-minute data.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
π‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Inspect callable tools, capabilities, and parameters exposed to AI agents by Indian NSE Stock Insights.
Indian NSE Stock Insights MCP server provides read-only market-analysis tools for stocks in the Nifty 500 universe. The tool set covers current quote data, historical OHLCV candles, technical indicators, support and resistance, demand and supply zones, candlestick and chart patterns, Fibonacci levels, volume analysis, market-wide summaries, stock comparisons, and filtered screening.
The server is intended for analysis and exploration rather than order placement or portfolio mutation. Its published disclaimer states that the information is educational only and is not investment advice. Symbols are supplied to individual stock tools, while comparison accepts two to five symbols and screening accepts filter criteria such as RSI, ADX, trend, pattern, or sector.
The hosted endpoint is available at https://stockmcp.alokbarnwal.com/mcp. An MCP client sends requests to the endpoint, and the server reads prepared market data from its database before returning tool results. yfinance supplies OHLCV data to scheduled update jobs; the application then exposes analysis results through FastMCP.
The supported timeframes are daily, 15min, and 5min. If a tool has an optional timeframe and none is supplied, it uses daily data. Published retention is five years for daily data, two years for 15-minute data, and six months for five-minute data. The dataset covers 500 stocks and is updated at end of day for daily data and during market hours for intraday data.
For a hosted connection, add a custom MCP connector with the server name Indian NSE Stock Insights and the URL above. The README specifically demonstrates connection through Claude.ai. No API key or other client credential is documented for that endpoint.
Self-hosting requires cloning the repository, creating a MySQL database named nse_public, applying the three SQL schema files, creating a Python virtual environment, and installing the dependencies from requirements.txt. The self-hosting instructions also require copying .env.example to .env and setting DB_PASSWORD to match the database user. After setup, operators can load the stock universe and backfill historical data. Scheduled cron jobs keep candles, indicators, and price-action data current.
The repository ships with approximately 100 stocks hardcoded; the provided stock configuration command can fetch the broader Nifty 500 list and load it into the database. Historical backfills and feature computation are separate, potentially long-running steps.
Indian NSE Stock Insights MCP server is limited to read operations. It does not document trading, brokerage, order-management, or portfolio tools. Results depend on the stored yfinance feed and the update jobs that populate the database.
The hosted service applies an nginx limit of 20 requests per second per IP, with a burst of 40, and allows 10 simultaneous connections per IP. Five rate-limit violations within two minutes can trigger a one-hour fail2ban ban. Market data follows NSE hours of 09:15β15:30 IST on weekdays, excluding NSE holidays. Treat the output as educational analysis, not investment advice.
Always refer to the official documentation for the most accurate and up-to-date information.
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