Server data from the Official MCP Registry
Analyze any Nifty 500 stock with AI — price action, demand zones, technicals & screener.
Analyze any Nifty 500 stock with AI — price action, demand zones, technicals & screener.
Remote endpoints: streamable-http: https://stockmcp.alokbarnwal.com/mcp
Valid MCP server (0 strong, 2 medium validity signals). 3 known CVEs in dependencies (0 critical, 1 high severity) Imported from the Official MCP Registry.
5 files analyzed · 3 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
This plugin requests these system permissions. Most are normal for its category.
Available as Local & Remote
This plugin can run on your machine or connect to a hosted endpoint. during install.
From the project's GitHub README.
Public MCP server for Indian stock market analysis — Nifty 500 universe, 12 tools, 3 timeframes.
Built with FastMCP · Data from yfinance · Hosted at stockmcp.alokbarnwal.com
Educational only. Not investment advice. See DISCLAIMER.md.
Claude.ai → Settings → Connectors → Add custom MCP connector:
Name: Indian NSE Stock Insights
URL: https://stockmcp.alokbarnwal.com/mcp
That's it. Start asking questions about Indian stocks.
| # | Tool | Parameters | What it returns |
|---|---|---|---|
| 1 | get_stock_quote | symbol | Last close, prev close, change %, day H/L, volume |
| 2 | get_ohlc_data | symbol, timeframe?, limit? | OHLCV candles (up to 500, newest first) |
| 3 | get_technical_indicators | symbol, timeframe? | EMAs, SMAs, RSI, MACD, Bollinger, ADX, Stoch, ATR, OBV, VWAP |
| 4 | get_support_resistance | symbol, timeframe? | Pivot points + historical S/R levels |
| 5 | get_demand_supply_zones | symbol, timeframe?, status? | Demand/supply zones (DBR/RBR/RBD/DBD) |
| 6 | get_candlestick_patterns | symbol, timeframe?, limit? | HAMMER, DOJI, ENGULFING, etc. |
| 7 | get_chart_patterns | symbol, timeframe?, status? | DOUBLE_TOP, HEAD_AND_SHOULDERS, etc. |
| 8 | get_fibonacci_levels | symbol, timeframe? | Retracement swings (UP/DOWN) with fib levels |
| 9 | get_volume_analysis | symbol | 5min hotspots, OBV trend, volume ratio |
| 10 | get_market_overview | (none) | Indices, top gainers/losers, most active, breadth |
| 11 | compare_stocks | symbols (2-5) , timeframe? | Side-by-side: quote, RSI/MACD/ADX, trend, 30d return |
| 12 | screen_stocks | filters | Filter by RSI, ADX, trend, pattern, sector, etc. |
timeframe defaults to daily. Options: daily, 15min, 5min.
Try these in Claude.ai after connecting:
graph TB
subgraph Internet
C[Claude.ai / MCP Client]
end
subgraph Server["Production Server"]
subgraph Protection
F2B[fail2ban<br/>auto-ban repeat abusers]
NG[nginx<br/>rate limit 20r/s · conn limit · TLS]
end
subgraph Application
MCP["FastMCP Server<br/>port 8089 · 12 tools"]
TOOLS["Tool Modules<br/>quote · ohlc · indicators<br/>levels · zones · patterns<br/>fibonacci · volume · market<br/>compare · screener"]
end
subgraph Data
DB[(MySQL: nse_public<br/>500 stocks × 3 timeframes)]
CRON[Cron Jobs<br/>5min · 15min · daily]
end
end
subgraph External
YF[Yahoo Finance<br/>yfinance API]
end
C -->|HTTPS POST /mcp| NG
NG -->|proxy_pass| MCP
MCP --> TOOLS
TOOLS -->|read-only queries| DB
YF -->|OHLCV data| CRON
CRON -->|upsert| DB
F2B -.->|monitors| NG
| Timeframe | Retention | Update Frequency | Stocks |
|---|---|---|---|
| Daily | 5 years | EOD (18:00 IST) | 500 |
| 15-minute | 2 years | Every 15 min (market hours) | 500 |
| 5-minute | 6 months | Every 5 min (market hours) | 500 |
Market hours: 09:15–15:30 IST, Monday–Friday (excluding NSE holidays).
| Layer | Limit | Action |
|---|---|---|
| nginx | 20 requests/sec per IP (burst 40) | HTTP 429 |
| nginx | 10 simultaneous connections per IP | HTTP 429 |
| fail2ban | 5× rate-limit violations in 2 min | IP banned for 1 hour |
Runs on
/home/ubuntu/nse-public-mcp/— completely isolated from/home/ubuntu/swingtrader/.
cd /home/ubuntu
git clone https://github.com/alokbarnwal/nse-public-mcp.git
cd nse-public-mcp
sudo mysql <<'SQL'
CREATE DATABASE IF NOT EXISTS nse_public CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci;
CREATE USER IF NOT EXISTS 'nse_writer'@'localhost' IDENTIFIED BY 'CHANGE_ME_STRONG_PASSWORD';
GRANT ALL PRIVILEGES ON nse_public.* TO 'nse_writer'@'localhost';
FLUSH PRIVILEGES;
SQL
mysql -u nse_writer -p nse_public < db/schema.sql
mysql -u nse_writer -p nse_public < db/schema_indicators.sql
mysql -u nse_writer -p nse_public < db/schema_price_action.sql
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
cp .env.example .env
chmod 600 .env
nano .env # set DB_PASSWORD to match step 2
The repo ships with the top ~100 stocks hardcoded. To expand to all 500:
python -m config.stocks --refresh # fetches NSE archives, rewrites config/stocks.py
python -m config.stocks --load-to-db
screen -S backfill
source .venv/bin/activate
python -m data.backfill --all
# Ctrl-A D to detach. Reattach: screen -r backfill
Expected runtime:
daily 5y × 500: ~30 min15min 2y × 500: ~2 h5min 6mo × 500: ~1 hIf anything fails, the failure list is written to backfill_failures_<timeframe>.json. Re-run:
python -m data.backfill --timeframe 15min --resume
After the candle backfill completes, populate the indicators table for all 500 stocks across all 3 timeframes:
screen -S indicators
cd /home/ubuntu/nse-public-mcp
python3 -m indicators.runner --all
# Ctrl-A D to detach
Expected runtime: ~30–45 min. Idempotent — safe to re-run if interrupted.
After indicators are populated, compute price-action features (zones, S/R, patterns, breakouts, fibs, gaps, volume profile) for all 500 stocks across all 3 timeframes:
screen -S price_action
cd /home/ubuntu/nse-public-mcp
python3 -m price_action.runner --timeframe daily --all-features
python3 -m price_action.runner --timeframe 15min --all-features
python3 -m price_action.runner --timeframe 5min --all-features
# Ctrl-A D to detach
Expected runtime: ~60–90 min total. Idempotent — safe to re-run if interrupted.
crontab -e
Add:
# nse-public-mcp candle updaters
*/5 9-15 * * 1-5 cd /home/ubuntu/nse-public-mcp && /home/ubuntu/nse-public-mcp/.venv/bin/python -m jobs.cron_5min >> logs/cron_5min.log 2>&1
*/15 9-15 * * 1-5 cd /home/ubuntu/nse-public-mcp && /home/ubuntu/nse-public-mcp/.venv/bin/python -m jobs.cron_15min >> logs/cron_15min.log 2>&1
0 18 * * 1-5 cd /home/ubuntu/nse-public-mcp && /home/ubuntu/nse-public-mcp/.venv/bin/python -m jobs.cron_daily >> logs/cron_daily.log 2>&1
# nse-public-mcp indicator updaters (each runs after the matching candle fetch)
30 18 * * 1-5 cd /home/ubuntu/nse-public-mcp && /usr/bin/python3 -m jobs.cron_indicators_daily >> logs/indicators_daily.log 2>&1
20,35,50 9-15 * * 1-5 cd /home/ubuntu/nse-public-mcp && /usr/bin/python3 -m jobs.cron_indicators_15min >> logs/indicators_15min.log 2>&1
5 16 * * 1-5 cd /home/ubuntu/nse-public-mcp && /usr/bin/python3 -m jobs.cron_indicators_15min >> logs/indicators_15min.log 2>&1
2-57/5 9-15 * * 1-5 cd /home/ubuntu/nse-public-mcp && /usr/bin/python3 -m jobs.cron_indicators_5min >> logs/indicators_5min.log 2>&1
# nse-public-mcp price-action updaters (each runs after the matching indicator cron)
35 18 * * 1-5 cd /home/ubuntu/nse-public-mcp && /usr/bin/python3 -m jobs.cron_price_action_daily >> logs/price_action_daily.log 2>&1
25,55 9-15 * * 1-5 cd /home/ubuntu/nse-public-mcp && /usr/bin/python3 -m jobs.cron_price_action_15min >> logs/price_action_15min.log 2>&1
9-54/15 9-15 * * 1-5 cd /home/ubuntu/nse-public-mcp && /usr/bin/python3 -m jobs.cron_price_action_5min >> logs/price_action_5min.log 2>&1
Cron times are server-local. Verify the server is on IST (
timedatectl) — if not, shift the hour ranges. The 5-min indicator cron is offset to2-57/5so it runs ~2 minutes aftercron_5minand never reads stale candles. The price-action 5-min cron is offset to9-54/15(minutes 9, 24, 39, 54) so it runs ~2 minutes after eachcron_indicators_5minslot.
mysql -u nse_writer -p nse_public <<'SQL'
SELECT 'daily' AS tf, COUNT(*) AS n FROM candles_daily
UNION ALL SELECT '15min', COUNT(*) FROM candles_15min
UNION ALL SELECT '5min', COUNT(*) FROM candles_5min;
-- Per-stock coverage on daily — flag any with < 1000 rows (~4 trading years)
SELECT symbol, COUNT(*) AS n
FROM candles_daily
GROUP BY symbol
HAVING n < 1000
ORDER BY n;
-- Latest data freshness
SELECT MIN(candle_date) AS earliest, MAX(candle_date) AS latest
FROM candles_daily;
-- Recent cron health
SELECT job_type, timeframe, symbols_success, symbols_failed, started_at, duration_seconds
FROM fetch_log
ORDER BY started_at DESC
LIMIT 20;
SQL
DB size on disk:
sudo du -sh /var/lib/mysql/nse_public/
# Server status
sudo systemctl status nse-public-mcp
# Restart
sudo systemctl restart nse-public-mcp
# Logs
sudo journalctl -u nse-public-mcp -n 100 -f
# nginx
sudo nginx -t && sudo systemctl reload nginx
# fail2ban
sudo fail2ban-client status nginx-mcp-ratelimit
See PROJECT.md for architecture and data-flow diagram.
config/ # settings, stock universe, holiday calendar
data/ # yfinance fetcher, backfill CLI, shared upsert helpers
db/ # schema and pooled connection
indicators/ # technical indicator compute, persist, runner
price_action/ # zones, patterns, levels, trends
mcp_server/ # FastMCP server + 12 tool modules
jobs/ # cron entrypoints (candles + indicators + price action)
deploy/ # systemd service, nginx config, fail2ban rules
tests/ # mocked unit tests (82 tests)
INSERT … ON DUPLICATE KEY UPDATE. Replaying a cron tick or rerunning backfill is safe.config/holidays.py. Update it once a year when NSE publishes the next year's list.jobs/cron_daily.py. Daily candles older than 5 y, 15min older than 2 y, 5min older than 6 mo are purged.MIT — free to use, modify, and distribute.
This project is for educational and informational purposes only. Not investment advice. See DISCLAIMER.md.
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