nsekit-mcp 0.0.28

FastMCP server for NSE India market data using NseKit

NseKit-MCP — NSE India Real-time & Historical Data Server

NseKit-MCP is a high-performance FastMCP (Model Context Protocol) server that exposes 100+ tools for accessing live and historical data from the National Stock Exchange of India (NSE) using the powerful NseKit Python library.

Perfect for AI agents (Claude, Grok, GPT, Gemini CLI etc.), trading bots, backtesters, and research platforms.

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Features

• 100+ ready-to-use tools
• Live & historical equity, F&O, indices, IPOs, corporate actions
• Full option chains with OI, Volume, IV, PCR, Max Pain
• EOD bhavcopy, delivery data, FII/DII, bulk/block deals
• Built-in NSE-safe rate limiting (~3 req/sec)
• Clean JSON output (Pandas → list of dicts)
• Works with Claude Desktop, Cursor, Cline, Windsurf, etc. via FastMCP

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Installation

Use this MCP server via uv (Python package installer)

pip install uv

Add the following configuration to your MCP server configuration file:

{
  "mcpServers": {
    "NseKit-MCP": {
      "command": "uvx",
      "args": ["nsekit-mcp@latest"]
    }
  }
}

Popular Tools

Tool	Description
market_live_status()	Market open/close, Nifty, Gift Nifty, Mcap
equity_live_stock_info("RELIANCE")	Live price + 5-level depth + delivery
fno_live_option_chain("NIFTY","27-Jan-2026")	Nifty/BankNifty option chain data
equity_eod_bhavcopy_delivery("02-12-2025")	Full day closing + delivery %
fii_dii_activity()	Latest FII/DII net buying/selling
ipo_current_list()	All live Mainboard + SME IPOs with subscription
equity_52week_high_live()	Stocks hitting 52-week high today

All tools return clean JSON arrays.

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Tool Categories

NSE_Live • Pre_Market • Index_Live • Equity_Live
FnO_Live • Corporate_Events • IPO • Historical
Equity_EOD • FnO_EOD • Regulatory (SEBI)

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Safety & Compliance

• Thread-safe rate limiting (0.35s delay between NSE calls)
• Respects NSE's fair usage policy
• For research, personal trading, and AI agent use only

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Credits

• Data powered by NseKit
• Server powered by FastMCP
• Made with ❤️ for the Indian Quant & Algo community