sip-advisor-mcp
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@sip-advisor-mcpGiven NIFTY's current valuation and trend, should I pause or step up my SIP?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Market-Aware SIP Timing Advisor — FastMCP (workshop)
A ~180-line Python MCP server that turns live NSE index data into an SIP step-up / pause recommendation. Built for the mfAPIs × SunitechAI webinar.
Design: the server owns no data. Raw NIFTY 50 PE and OHLC rows come from the MF Engine REST API; the valuation-percentile, price-trend and SIP-rule logic live here in Python. That split is the teachable part.
Tool | What it does |
| current PE + percentile + z-score vs 10y history → cheap / fair / expensive |
| DMA50/200, distance from 52w high/low, 1/3/6m returns → uptrend / sideways / downtrend |
| band (+ trend) → pause / continue / step_up + suggested new amount |
Setup
cd workshop/sip-advisor-mcp
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt
cp .env.example .env # then paste MFAPI_TOKENMFAPI_TOKEN is a JWT access-token for a partner / investor / admin user.
Get it from the zinni-app browser session (DevTools → Application → Local
Storage, or the Network tab) or a login API call. It is not the MCP static
token — the REST endpoints use normal user auth.
Related MCP server: Sentimatix
Run
# stdio — for Claude Desktop
python server.py
# HTTP — for ChatGPT developer mode / remote clients (serves :8000/mcp)
MCP_TRANSPORT=http python server.pyQuick check without an LLM:
pip install fastmcp # includes the CLI
fastmcp run server.py --transport http &
npx @modelcontextprotocol/inspector # connect to http://localhost:8000/mcpConnect to Claude
Claude Desktop — merge claude_desktop_config.example.json into
~/Library/Application Support/Claude/claude_desktop_config.json (fix the
absolute path + token), restart Claude Desktop.
Claude Code
claude mcp add sip-advisor -- python /abs/path/workshop/sip-advisor-mcp/server.py
# set MFAPI_TOKEN in the shell that launches claude, or via --envConnect to ChatGPT
Run in HTTP mode, expose it (cloudflared tunnel --url http://localhost:8000
or ngrok http 8000), then Settings → Connectors → Advanced → Developer
mode → Add the https://…/mcp URL. Regular ChatGPT connectors need
search/fetch tools; this server works via developer mode or the
Responses API only.
Demo script
"I run a ₹10,000/month NIFTY 50 SIP. Given where the market is, should I step it up, hold, or pause?"
The model chains get_nifty_valuation_context → get_nifty_trend →
recommend_sip_action(band, trend, 10000) and explains the call with the PE
percentile, the trend, and the as_of date.
Note on data freshness
The prod NSE OHLC / valuation tables can lag the live market by weeks. The
tools return as_of — always read it out in the demo, and fix the ingestion
in the data repo before going live.
This server cannot be deployed
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