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mcp/client/host.py

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+#!/usr/bin/env python3
+"""
+CLI host for the FastAPI-powered Swiggy server.
+
+Flow
+1. Send natural-language query → /parse_query
+2. If is_swiggy_query == True and dates are present → /get_orders
+3. Pretty-print the result
+"""
+
+import requests, sys
+from dateutil import parser as dtparse
+
+API_BASE = "http://127.0.0.1:8000"
+
+# ----------------------------------------------------------------------
+# Helpers
+# ----------------------------------------------------------------------
+def nice_date(dt_str: str | None) -> str:
+    if not dt_str:
+        return "??"
+    return dtparse.parse(dt_str).strftime("%d %b %Y")
+
+def pretty_order(order: dict) -> str:
+    if "error" in order:
+        return f"  - Email #{order['email_number']}: ❌  {order['error']}"
+    head = (
+        f"Restaurant : {order['restaurant_name']}\n"
+        f"Date       : {nice_date(order['order_date'])} {order['order_time']}\n"
+        f"Total      : ₹{order['total_price']:.0f}\n"
+        "Items:"
+    )
+    items = "\n".join(
+        f"   • {it['quantity']} × {it['name']} – ₹{it['price']:.0f}"
+        for it in order["items"]
+    )
+    return head + "\n" + items
+
+# ----------------------------------------------------------------------
+# Main REPL
+# ----------------------------------------------------------------------
+def main() -> None:
+    # Quick health-check
+    try:
+        requests.get(f"{API_BASE}/docs").raise_for_status()
+    except Exception as e:
+        print("❌  Cannot reach FastAPI server:", e)
+        sys.exit(1)
+    print("✅  Connected. Type a Swiggy question (or Ctrl-C to quit).")
+
+    while True:
+        try:
+            query = input("\n🗨️  You: ").strip()
+        except (EOFError, KeyboardInterrupt):
+            break
+        if not query:
+            continue
+
+        # ── Stage 1: parse_query ────────────────────────────────────
+        try:
+            r = requests.post(f"{API_BASE}/parse_query", json={"query": query})
+            r.raise_for_status()
+            meta = r.json()          # {is_swiggy_query, start_date, end_date, intent}
+        except Exception as e:
+            print("⚠️  Parse error:", e)
+            print("🔎  Server:", r.text if 'r' in locals() else "no response")
+            continue
+
+        # Handle non-Swiggy or missing dates
+        if not meta.get("is_swiggy_query"):
+            print("🤷  That doesn’t look like a Swiggy order query.")
+            continue
+        if not meta.get("start_date") or not meta.get("end_date"):
+            print("⚠️  Couldn’t find a full date range in your question.")
+            continue
+
+        print(f"   ↳ Date range: {meta['start_date']} → {meta['end_date']}")
+        print(f"   ↳ Intent    : {meta['intent']}")
+
+        # ── Stage 2: get_orders ────────────────────────────────────
+        try:
+            r2 = requests.post(
+                f"{API_BASE}/get_orders",
+                json={
+                    "start_date": meta["start_date"],
+                    "end_date":   meta["end_date"],
+                },
+            )
+            r2.raise_for_status()
+            orders = r2.json()
+        except Exception as e:
+            print("⚠️  Failed to fetch orders:", e)
+            print("🔎  Server:", r2.text if 'r2' in locals() else "no response")
+            continue
+
+        # ── Output ────────────────────────────────────────────────
+        if not orders:
+            print("😕  No orders found for that range.")
+            continue
+
+        print("\n📦  Orders:")
+        for o in orders:
+            print(pretty_order(o))
+            print("-" * 40)
+
+    print("\n👋  Bye!")
+
+# ----------------------------------------------------------------------
+if __name__ == "__main__":
+    main()

mcp/server/db_schema.py

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+# File: db_schema.py
+import sqlite3
+
+DB_NAME = "swiggy_orders.db"
+
+
+def init_db(db_path: str = DB_NAME) -> None:
+    """
+    Initialize the SQLite database with the necessary tables.
+    """
+    conn = sqlite3.connect(db_path)
+    c = conn.cursor()
+    # Orders metadata
+    c.execute(
+        """
+        CREATE TABLE IF NOT EXISTS orders (
+            id INTEGER PRIMARY KEY AUTOINCREMENT,
+            email_number INTEGER,
+            order_date TEXT,
+            order_time TEXT,
+            restaurant_name TEXT,
+            delivery_address TEXT,
+            total_price REAL
+        )
+        """
+    )
+    # Individual items per order
+    c.execute(
+        """
+        CREATE TABLE IF NOT EXISTS order_items (
+            id INTEGER PRIMARY KEY AUTOINCREMENT,
+            order_id INTEGER,
+            item_name TEXT,
+            quantity INTEGER,
+            price REAL,
+            FOREIGN KEY(order_id) REFERENCES orders(id)
+        )
+        """
+    )
+    conn.commit()
+    conn.close()
+
+
+def get_db_connection(db_path: str = DB_NAME) -> sqlite3.Connection:
+    """Return a new connection to the database."""
+    return sqlite3.connect(db_path)
+
+
+def get_orders_by_date_from_db(date_str: str) -> list[dict]:
+    """
+    Fetch all orders and their items for a given date from the database.
+    """
+    conn = get_db_connection()
+    c = conn.cursor()
+    c.execute(
+        "SELECT id, email_number, order_time, restaurant_name, delivery_address, total_price"
+        " FROM orders WHERE order_date = ?",
+        (date_str,)
+    )
+    orders = []
+    for order_id, email_number, order_time, restaurant_name, delivery_address, total_price in c.fetchall():
+        # fetch items for this order
+        c.execute(
+            "SELECT item_name, quantity, price FROM order_items WHERE order_id = ?",
+            (order_id,)
+        )
+        items = [
+            {"name": name, "quantity": qty, "price": price}
+            for name, qty, price in c.fetchall()
+        ]
+        orders.append({
+            "email_number": email_number,
+            "order_date": date_str,
+            "order_time": order_time,
+            "restaurant_name": restaurant_name,
+            "delivery_address": delivery_address,
+            "items": items,
+            "total_price": total_price
+        })
+    conn.close()
+    return orders
+
+
+def save_orders_to_db(date_str: str, orders: list[dict]) -> None:
+    """
+    Insert scraped orders and their items for a given date into the database.
+    """
+    conn = get_db_connection()
+    c = conn.cursor()
+    for order in orders:
+        c.execute(
+            """
+            INSERT INTO orders
+                (email_number, order_date, order_time, restaurant_name, delivery_address, total_price)
+            VALUES (?, ?, ?, ?, ?, ?)
+            """,
+            (
+                order["email_number"],
+                date_str,
+                order["order_time"],
+                order["restaurant_name"],
+                order["delivery_address"],
+                order["total_price"]
+            )
+        )
+        order_id = c.lastrowid
+        for item in order.get("items", []):
+            c.execute(
+                """
+                INSERT INTO order_items
+                    (order_id, item_name, quantity, price)
+                VALUES (?, ?, ?, ?)
+                """,
+                (
+                    order_id,
+                    item["name"],
+                    item["quantity"],
+                    item["price"]
+                )
+            )
+    conn.commit()
+    conn.close()
+
+

mcp/server/eval.txt

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+EVALUATIONS
+
+able to differentiate between swiggy based queries or not
+able to break prompts into 2 instruction. First instruction will be extracting dates. 
+second instructions will be analysing the data scrapped.  
+able to extract dates
+able to extract the analysis:
+
+-How much non-veg did I order last week / between date X and date Y?
+
+-Counts and/or total rupees spent on non-veg dishes.
+
+-What was my total expense between date X and date Y?
+
+-What is my average daily spend on Swiggy (overall or for a given period)?
+
+-Which restaurant got the most orders (or the most money) in that period?
+
+-What single order cost me the most during that window?
+
+-Show a day-by-day spend chart between date X and date Y.
+
+-List every item I’ve ordered only once—my “one-hit wonders.”
+
+-How many unique cuisines did I try in the last month?
+
+-Compare veg vs. non-veg spend for the current calendar year.
+
+-When was my longest streak of days without ordering anything?
+
+-Identify any “late-night” orders placed after 11 p.m. this week.
+
+-Tell me my top three most-ordered dishes in the past six months.
+
+-Which new restaurant did I try most recently, and what did I order?
+
+-Forecast next month’s spend based on my last three-month trend.

mcp/server/main.py

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+# File: main.py
+from fastapi import FastAPI
+from contextlib import asynccontextmanager
+from routes import router
+from db_schema import init_db
+
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    print("🚀 Server is starting up...")
+    # Ensure SQLite tables exist before handling requests
+    init_db()
+    yield
+    print("🧹 Server is shutting down... Cleaned up!")
+
+app = FastAPI(
+    title="Swiggy Email API",
+    description="Extract Swiggy orders from Gmail",
+    version="1.0.0",
+    lifespan=lifespan
+)
+
+app.include_router(router)
+
+# Run with: uvicorn main:app --reload

mcp/server/routes.py

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+from fastapi import APIRouter, HTTPException
+from pydantic import BaseModel
+from swiggy_scraper import fetch_swiggy_orders
+from datetime import datetime
+from openai import OpenAI
+import os, json
+
+router = APIRouter()
+client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
+
+class QueryInput(BaseModel):
+    query: str
+
+class DateRange(BaseModel):
+    start_date: str
+    end_date: str
+
+# @router.post("/parse_query")
+# def parse_query_llm(input: QueryInput):
+
+#     print("\ninput query:")
+#     print(input)
+
+#     today_str = datetime.today().strftime("%d-%b-%Y")
+#     system = (
+#         f"You are a date range extractor.\n"
+#         f"Today is {today_str}.\n"
+#         "Extract start_date and end_date in 'DD-MMM-YYYY' format.\n"
+#         "Respond with:\n"
+#         "Output ONLY a valid JSON object like:\n"
+#         '{ "start_date": "17-May-2025", "end_date": "18-May-2025" }\n'
+#         'no extra commentry needed.'
+#     )
+#     try:
+#         rsp = client.chat.completions.create(
+#             model="gpt-4o-mini",
+#             temperature=0,
+#             messages=[
+#                 {"role": "system", "content": system},
+#                 {"role": "user", "content": input.query},
+#             ]
+#         )
+#         result = json.loads(rsp.choices[0].message.content.strip())
+#         if "start_date" not in result or "end_date" not in result:
+#             raise ValueError("Invalid response format")
+#         print("results:", result)
+#         return result
+#     except Exception as e:
+#         raise HTTPException(status_code=400, detail=str(e))
+
+
+
+
+
+
+
+def _llm(messages, model="gpt-4o-mini", temperature=0):
+    rsp = client.chat.completions.create(
+        model=model,
+        temperature=temperature,
+        messages=messages,
+    )
+    return rsp.choices[0].message.content.strip()
+
+# ----------  Stage 1: classify + extract dates --------------------------
+
+def _extract_scope(user_query: str):
+    today_str = datetime.today().strftime("%d-%b-%Y")
+
+    sys_prompt = f"""
+Today is {today_str}.
+You are a SCOPING assistant: decide if the user's text is about Swiggy food orders,
+extract ONE date range, and keep the leftover words.
+
+Return ONLY valid JSON like:
+{{
+  "is_swiggy_query": true,
+  "start_date": "15-May-2025",
+  "end_date":   "20-May-2025",
+  "remainder":  "non veg expense"
+}}
+
+Rules:
+• Accept natural phrases (“last week”, “since 1 May”).  
+• If no dates → start_date & end_date = null.  
+• If not Swiggy related → is_swiggy_query=false and remainder is full original text.  
+• Do NOT invent a remainder; it is literally whatever words follow the date phrase(s).  
+"""
+    raw = _llm(
+        [
+            {"role": "system", "content": sys_prompt},
+            {"role": "user",   "content": user_query}
+        ]
+    )
+    return json.loads(raw)
+
+# ----------  Stage 2: shrink “remainder” into an intent -----------------
+
+def _extract_intent(remainder: str):
+    sys_prompt = """
+You are an INTENT classifier for Swiggy-order analytics.
+Map the sentence into one concise snake_case intent.
+Allowed intents (extendable):
+
+• calculate_expense
+• list_orders
+• list_items
+• list_nonveg_items
+• list_veg_items
+• count_orders
+• unknown
+
+Return JSON: { "intent": "calculate_expense" }
+If unsure choose "unknown".
+"""
+    raw = _llm(
+        [
+            {"role": "system", "content": sys_prompt},
+            {"role": "user",   "content": remainder.strip()}
+        ]
+    )
+    return json.loads(raw)["intent"]
+
+# ----------  FastAPI route ----------------------------------------------
+
+@router.post("/parse_query")
+def parse_query_llm(input: QueryInput):
+    try:
+        scope = _extract_scope(input.query)
+        print("scope")
+        print(scope)
+        # If it is a Swiggy query, classify intent; else, intent = "unrelated"
+        if scope.get("is_swiggy_query", False):
+            intent = _extract_intent(scope.get("remainder", ""))
+        else:
+            intent = "unrelated"
+
+        result = {
+            "is_swiggy_query": scope["is_swiggy_query"],
+            "start_date":      scope["start_date"],
+            "end_date":        scope["end_date"],
+            "intent":          intent
+        }
+
+
+        print("result")
+        print(result)
+
+        return result
+
+    except Exception as e:
+        raise HTTPException(status_code=400, detail=str(e))
+
+
+
+
+
+
+
+
+@router.post("/get_orders")
+def get_orders(range: DateRange):
+    try:
+        orders = fetch_swiggy_orders(range.start_date, range.end_date)
+        return orders
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))

mcp/server/swiggy_cache.json

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+{
+  "2025-05-17": [
+    {
+      "email_number": 1,
+      "order_date": "17-May-2025",
+      "order_time": "11:00:08",
+      "restaurant_name": "IDC Kitchen",
+      "delivery_address": "2C, Orchard Green Apartment, 2nd Main Rd, Domlur, Bangalore, Karnataka 560071, India. (Orchard Green)",
+      "items": [
+        {
+          "name": "Thatte Idli",
+          "quantity": 1,
+          "price": 59
+        },
+        {
+          "name": "Idly 2 Pc",
+          "quantity": 1,
+          "price": 59
+        },
+        {
+          "name": "Vada (1 Pc)",
+          "quantity": 3,
+          "price": 174
+        }
+      ],
+      "total_price": 330
+    },
+    {
+      "email_number": 2,
+      "order_date": "17-May-2025",
+      "order_time": "17:02:59",
+      "restaurant_name": "Suryawanshi",
+      "delivery_address": "Shobhit\n2C, Orchard Green Apartment\n2nd Main Rd, Domlur, Bangalore, Karnataka 560071, India. (Orchard Green)",
+      "items": [
+        {
+          "name": "Vada Pav (twin)",
+          "quantity": 1,
+          "price": 95
+        },
+        {
+          "name": "Kande Bhaji",
+          "quantity": 1,
+          "price": 160
+        }
+      ],
+      "total_price": 300
+    },
+    {
+      "email_number": 3,
+      "order_date": "17-May-2025",
+      "order_time": "20:25:39",
+      "restaurant_name": "Meghana Foods",
+      "delivery_address": "2C, Orchard Green Apartment, 2nd Main Rd, Domlur, Bangalore, Karnataka 560071, India. (Orchard Green)",
+      "items": [
+        {
+          "name": "Extra Aloo 4 Pcs",
+          "quantity": 1,
+          "price": 45
+        },
+        {
+          "name": "Chicken Boneless Biryani",
+          "quantity": 1,
+          "price": 360
+        },
+        {
+          "name": "Lemon Chicken",
+          "quantity": 1,
+          "price": 360
+        },
+        {
+          "name": "Veg Manchurian Biryani",
+          "quantity": 1,
+          "price": 360
+        }
+      ],
+      "total_price": 1240
+    }
+  ],
+  "2025-05-19": [
+    {
+      "email_number": 1,
+      "order_date": "19-May-2025",
+      "order_time": "22:28:08",
+      "restaurant_name": "Swiggy Instamart",
+      "delivery_address": "2C, Orchard Green Apartment  2nd Main Rd, Domlur, Bangalore, Karnataka 560071, India. (Orchard Green)",
+      "items": [
+        {
+          "name": "Safal Frozen Green Peas (Matar)",
+          "quantity": 1,
+          "price": 110
+        },
+        {
+          "name": "NOTO Strawberry Raspberry Sugar Free Popsicle Ice Cream",
+          "quantity": 4,
+          "price": 500
+        },
+        {
+          "name": "Baby Lady's Finger  (Bendekaayi)",
+          "quantity": 2,
+          "price": 32
+        },
+        {
+          "name": "Whisper Ultra Skin Love Soft 30 Xl+ Sanitary Pads, Cottony Soft",
+          "quantity": 1,
+          "price": 323
+        },
+        {
+          "name": "Akshayakalpa Artisanal Organic Set Curd",
+          "quantity": 1,
+          "price": 145
+        },
+        {
+          "name": "Akshayakalpa Organic Malai Paneer",
+          "quantity": 1,
+          "price": 119
+        },
+        {
+          "name": "Aashirvaad Superior MP Atta",
+          "quantity": 2,
+          "price": 146
+        },
+        {
+          "name": "NOTO Kala Jamun Sugar Free Popsicle Ice Cream",
+          "quantity": 2,
+          "price": 250
+        },
+        {
+          "name": "Royal Gala Apple (Sebu)",
+          "quantity": 2,
+          "price": 356
+        }
+      ],
+      "total_price": 1564
+    }
+  ],
+  "2025-05-01": [
+    {
+      "email_number": 1,
+      "order_date": "01-May-2025",
+      "order_time": "11:36:15",
+      "restaurant_name": "Starbucks Coffee",
+      "delivery_address": "2C, Orchard Green Apartment, 2nd Main Rd, Domlur, Bangalore, Karnataka 560071, India. (Orchard Green)",
+      "items": [
+        {
+          "name": "Caffe Americano",
+          "quantity": 2,
+          "price": 710
+        }
+      ],
+      "total_price": 647
+    },
+    {
+      "email_number": 2,
+      "order_date": "01-May-2025",
+      "order_time": "18:34:08",
+      "restaurant_name": "Chaayos Chai+Snacks=Relax",
+      "delivery_address": "Shobhit\n2C, Orchard Green Apartment\n2nd Main Rd, Domlur, Bangalore, Karnataka 560071, India. (Orchard Green)",
+      "items": [
+        {
+          "name": "Vada Pav",
+          "quantity": 2,
+          "price": 238
+        },
+        {
+          "name": "Desi Chai",
+          "quantity": 1,
+          "price": 219
+        },
+        {
+          "name": "Samosa(2 pc)",
+          "quantity": 1,
+          "price": 90
+        }
+      ],
+      "total_price": 528
+    },
+    {
+      "email_number": 3,
+      "order_date": "01-May-2025",
+      "order_time": "21:28:12",
+      "restaurant_name": "Lavonne Cafe",
+      "delivery_address": "2C, Orchard Green Apartment, 2nd Main Rd, Domlur, Bangalore, Karnataka 560071, India. (Orchard Green)",
+      "items": [
+        {
+          "name": "Baguette",
+          "quantity": 1,
+          "price": 190.48
+        }
+      ],
+      "total_price": 278
+    }
+  ],
+  "2025-05-02": [
+    {
+      "email_number": 1,
+      "order_date": "02-May-2025",
+      "order_time": "11:13:38",
+      "restaurant_name": "Starbucks Coffee",
+      "delivery_address": "2C, Orchard Green Apartment, 2nd Main Rd, Domlur, Bangalore, Karnataka 560071, India. (Orchard Green)",
+      "items": [
+        {
+          "name": "Caffe Americano",
+          "quantity": 1,
+          "price": 315
+        },
+        {
+          "name": "Caffe Americano",
+          "quantity": 1,
+          "price": 355
+        }
+      ],
+      "total_price": 605
+    },
+    {
+      "email_number": 2,
+      "order_date": "02-May-2025",
+      "order_time": "14:43:19",
+      "restaurant_name": "Harvest Salad Co",
+      "delivery_address": "2C, Orchard Green Apartment, 2nd Main Rd, Domlur, Bangalore, Karnataka 560071, India. (Orchard Green)",
+      "items": [
+        {
+          "name": "Hummus And Chipotle Chicken Wrap",
+          "quantity": 2,
+          "price": 498
+        },
+        {
+          "name": "Mediterranean Bowl (Veg)",
+          "quantity": 1,
+          "price": 299
+        }
+      ],
+      "total_price": 899
+    },
+    {
+      "email_number": 3,
+      "order_date": "02-May-2025",
+      "order_time": "21:10:20",
+      "restaurant_name": "Swiggy Instamart",
+      "delivery_address": "2C, Orchard Green Apartment  2nd Main Rd, Domlur, Bangalore, Karnataka 560071, India. (Orchard Green)",
+      "items": [
+        {
+          "name": "Classic Ice Burst",
+          "quantity": 1,
+          "price": 170
+        }
+      ],
+      "total_price": 222
+    },
+    {
+      "email_number": 4,
+      "order_date": "02-May-2025",
+      "order_time": "22:01:35",
+      "restaurant_name": "Dhaba Estd 1986 Delhi",
+      "delivery_address": "2C, Orchard Green Apartment, 2nd Main Rd, Domlur, Bangalore, Karnataka 560071, India. (Orchard Green)",
+      "items": [
+        {
+          "name": "Non Vegetarian Platter ( 12 Pcs)",
+          "quantity": 1,
+          "price": 1249
+        },
+        {
+          "name": "Butter Naan",
+          "quantity": 2,
+          "price": 198
+        },
+        {
+          "name": "Dhabe Di Roti",
+          "quantity": 2,
+          "price": 238
+        },
+        {
+          "name": "Laal Mirchi Parantha",
+          "quantity": 1,
+          "price": 109
+        },
+        {
+          "name": "Handi Murgh",
+          "quantity": 1,
+          "price": 629
+        }
+      ],
+      "total_price": 2006
+    }
+  ],
+  "2025-05-03": [
+    {
+      "email_number": 1,
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+        {
+          "name": "Coin Parotta",
+          "quantity": 2,
+          "price": 64
+        },
+        {
+          "name": "Dal Fry",
+          "quantity": 1,
+          "price": 137
+        },
+        {
+          "name": "Ghee Rice",
+          "quantity": 1,
+          "price": 110
+        },
+        {
+          "name": "Malabar Parotta",
+          "quantity": 2,
+          "price": 70
+        }
+      ],
+      "total_price": 749
+    }
+  ],
+  "2025-05-12": [
+    {
+      "email_number": 1,
+      "order_date": "12-May-2025",
+      "order_time": "22:12:42",
+      "restaurant_name": "Swiggy Instamart",
+      "delivery_address": "2C, Orchard Green Apartment  2nd Main Rd, Domlur, Bangalore, Karnataka 560071, India. (Orchard Green)",
+      "items": [
+        {
+          "name": "NOTO Strawberry Raspberry Sugar Free Popsicle Ice Cream",
+          "quantity": 4,
+          "price": 275
+        },
+        {
+          "name": "NOTO Orange Sugar Free Popsicle Ice Cream",
+          "quantity": 2,
+          "price": 137.5
+        }
+      ],
+      "total_price": 423
+    }
+  ],
+  "2025-05-13": [],
+  "2025-05-14": [
+    {
+      "email_number": 1,
+      "order_date": "14-May-2025",
+      "order_time": "14:14:14",
+      "restaurant_name": "Swiggy Instamart",
+      "delivery_address": "2C, Orchard Green Apartment  2nd Main Rd, Domlur, Bangalore, Karnataka 560071, India. (Orchard Green)",
+      "items": [
+        {
+          "name": "Robusta Banana (Pachha Baalehannu)",
+          "quantity": 1,
+          "price": 42
+        },
+        {
+          "name": "Coriander - Without Roots (Kotthambari)",
+          "quantity": 1,
+          "price": 18
+        },
+        {
+          "name": "Tata Sampann Turmeric Powder Masala",
+          "quantity": 2,
+          "price": 85.04
+        },
+        {
+          "name": "Organic Certified Onion (Eerulli)",
+          "quantity": 1,
+          "price": 66
+        },
+        {
+          "name": "NOTO Strawberry Raspberry Sugar Free Popsicle Ice Cream",
+          "quantity": 4,
+          "price": 275
+        },
+        {
+          "name": "Premium Guava (Thai)",
+          "quantity": 2,
+          "price": 154
+        },
+        {
+          "name": "Garlic (Bellulli)",
+          "quantity": 1,
+          "price": 47
+        },
+        {
+          "name": "Royal Gala Apple (Sebu)",
+          "quantity": 1,
+          "price": 142
+        }
+      ],
+      "total_price": 841
+    }
+  ],
+  "2025-05-15": [],
+  "2025-05-16": [
+    {
+      "email_number": 1,
+      "order_date": "16-May-2025",
+      "order_time": "15:43:43",
+      "restaurant_name": "Glen's Bakehouse",
+      "delivery_address": "2C, Orchard Green Apartment, 2nd Main Rd, Domlur, Bangalore, Karnataka 560071, India. (Orchard Green)",
+      "items": [
+        {
+          "name": "Mushroom Puff",
+          "quantity": 1,
+          "price": 62.86
+        },
+        {
+          "name": "Chicken Puff",
+          "quantity": 1,
+          "price": 84.23
+        }
+      ],
+      "total_price": 235
+    },
+    {
+      "email_number": 2,
+      "order_date": "16-May-2025",
+      "order_time": "15:48:57",
+      "restaurant_name": "The Himalayan Momo Company",
+      "delivery_address": "2C, Orchard Green Apartment, 2nd Main Rd, Domlur, Bangalore, Karnataka 560071, India. (Orchard Green)",
+      "items": [
+        {
+          "name": "Woked Maggi",
+          "quantity": 1,
+          "price": 209
+        },
+        {
+          "name": "Himalayan Steamed Chicken Momos",
+          "quantity": 2,
+          "price": 318
+        }
+      ],
+      "total_price": 547
+    }
+  ],
+  "2025-05-18": [
+    {
+      "email_number": 1,
+      "order_date": "18-May-2025",
+      "order_time": "12:57:21",
+      "restaurant_name": "Starbucks Coffee",
+      "delivery_address": "2C, Orchard Green Apartment, 2nd Main Rd, Domlur, Bangalore, Karnataka 560071, India. (Orchard Green)",
+      "items": [
+        {
+          "name": "Caffe Americano",
+          "quantity": 1,
+          "price": 315
+        }
+      ],
+      "total_price": 363
+    },
+    {
+      "email_number": 2,
+      "order_date": "18-May-2025",
+      "order_time": "13:02:51",
+      "restaurant_name": "Maiz Mexican Kitchen",
+      "delivery_address": "2C, Orchard Green Apartment, 2nd Main Rd, Domlur, Bangalore, Karnataka 560071, India. (Orchard Green)",
+      "items": [
+        {
+          "name": "Chips With Guacamole",
+          "quantity": 1,
+          "price": 249
+        },
+        {
+          "name": "Fresh Tomato Salsa (50ml)",
+          "quantity": 1,
+          "price": 69
+        },
+        {
+          "name": "Chipotle Chicken Burrito",
+          "quantity": 1,
+          "price": 299
+        }
+      ],
+      "total_price": 491
+    }
+  ],
+  "2025-05-20": [
+    {
+      "email_number": 1,
+      "order_date": "20-May-2025",
+      "order_time": "11:24:05",
+      "restaurant_name": "IDC Kitchen",
+      "delivery_address": "2C, Orchard Green Apartment, 2nd Main Rd, Domlur, Bangalore, Karnataka 560071, India. (Orchard Green)",
+      "items": [
+        {
+          "name": "Vada (1 Pc)",
+          "quantity": 1,
+          "price": 58
+        },
+        {
+          "name": "Masala Dosa",
+          "quantity": 1,
+          "price": 140
+        }
+      ],
+      "total_price": 167
+    },
+    {
+      "email_number": 2,
+      "order_date": "20-May-2025",
+      "order_time": "16:15:50",
+      "restaurant_name": "Irani Std. Tea",
+      "delivery_address": "2C, Orchard Green Apartment, 2nd Main Rd, Domlur, Bangalore, Karnataka 560071, India. (Orchard Green)",
+      "items": [
+        {
+          "name": "Bun Omelette",
+          "quantity": 1,
+          "price": 139
+        },
+        {
+          "name": "Osmania Biscuits 100 Grams",
+          "quantity": 1,
+          "price": 100
+        },
+        {
+          "name": "Plain Maggie",
+          "quantity": 1,
+          "price": 119
+        },
+        {
+          "name": "Bun Maska",
+          "quantity": 1,
+          "price": 79
+        },
+        {
+          "name": "Irani Ginger Chai",
+          "quantity": 1,
+          "price": 219
+        },
+        {
+          "name": "Aloo Samosa",
+          "quantity": 1,
+          "price": 49
+        }
+      ],
+      "total_price": 627
+    },
+    {
+      "email_number": 3,
+      "order_date": "20-May-2025",
+      "order_time": "20:13:33",
+      "restaurant_name": "Gayatri Sandwich(Mithibai College)",
+      "delivery_address": "Shobhit, ground floor, Vile Parle East, Vile Parle, Mumbai, Maharashtra, India. (T1)",
+      "items": [
+        {
+          "name": "Sada Sandwich",
+          "quantity": 1,
+          "price": 50
+        },
+        {
+          "name": "Vada Pav",
+          "quantity": 1,
+          "price": 25
+        }
+      ],
+      "total_price": 178
+    }
+  ],
+  "2025-05-21": [
+    {
+      "email_number": 1,
+      "order_date": "21-May-2025",
+      "order_time": "12:56:56",
+      "restaurant_name": "Starbucks Coffee",
+      "delivery_address": "Shobhit\n2C, Orchard Green Apartment\n2nd Main Rd, Domlur, Bangalore, Karnataka 560071, India. (Orchard Green)",
+      "items": [
+        {
+          "name": "Cold Brew Black (Cold Brew)",
+          "quantity": 1,
+          "price": 390
+        }
+      ],
+      "total_price": 401
+    },
+    {
+      "email_number": 2,
+      "order_date": "21-May-2025",
+      "order_time": "12:58:49",
+      "restaurant_name": "Starbucks Coffee",
+      "delivery_address": "2C, Orchard Green Apartment, 2nd Main Rd, Domlur, Bangalore, Karnataka 560071, India. (Orchard Green)",
+      "items": [
+        {
+          "name": "Caffe Americano",
+          "quantity": 1,
+          "price": 315
+        }
+      ],
+      "total_price": 363
+    },
+    {
+      "email_number": 3,
+      "order_date": "21-May-2025",
+      "order_time": "22:07:56",
+      "restaurant_name": "Magnolia Bakery",
+      "delivery_address": "2C, Orchard Green Apartment, 2nd Main Rd, Domlur, Bangalore, Karnataka 560071, India. (Orchard Green)",
+      "items": [
+        {
+          "name": "Chocolate Cake with Chocolate Buttercream Cake Slice",
+          "quantity": 1,
+          "price": 260
+        },
+        {
+          "name": "CLASSIC TRES LECHES",
+          "quantity": 1,
+          "price": 410
+        }
+      ],
+      "total_price": 850
+    }
+  ],
+  "2025-05-22": [
+    {
+      "email_number": 1,
+      "order_date": "22-May-2025",
+      "order_time": "12:00:34",
+      "restaurant_name": "Yogisthaan",
+      "delivery_address": "2C, Orchard Green Apartment, 2nd Main Rd, Domlur, Bangalore, Karnataka 560071, India. (Orchard Green)",
+      "items": [
+        {
+          "name": "Poha (quick Of Breakfast)",
+          "quantity": 1,
+          "price": 288
+        },
+        {
+          "name": "Tapioca (sabu Dana) Khichadi",
+          "quantity": 1,
+          "price": 252
+        }
+      ],
+      "total_price": 547
+    }
+  ],
+  "2025-05-23": []
+}

mcp/server/swiggy_scraper.py

@@ -0,0 +1,179 @@
+"""
+Reusable helper to fetch Swiggy order e-mails and return a list[dict].
+
+Usage:
+    from swiggy_scraper import fetch_swiggy_orders
+    orders = fetch_swiggy_orders("17-May-2025", "20-May-2025")
+"""
+
+import os, imaplib, json
+from email import message_from_bytes
+from bs4 import BeautifulSoup
+from openai import OpenAI
+from dotenv import load_dotenv
+from datetime import datetime, timedelta
+from email.utils import parsedate_to_datetime
+from zoneinfo import ZoneInfo
+
+from db_schema import init_db, get_orders_by_date_from_db, save_orders_to_db
+
+
+load_dotenv()
+
+APP_PASSWORD = os.getenv("APP_PASSWORD")
+EMAIL_ID     = os.getenv("EMAIL_ID")
+OPENAI_KEY   = os.getenv("OPENAI_API_KEY")
+
+client = OpenAI(api_key=OPENAI_KEY)
+
+def _imap_connect():
+    m = imaplib.IMAP4_SSL("imap.gmail.com")
+    m.login(EMAIL_ID, APP_PASSWORD)
+    m.select('"[Gmail]/All Mail"')
+    return m
+
+def _email_to_clean_text(msg):
+    html = next(
+        (part.get_payload(decode=True).decode(errors="ignore")
+         for part in msg.walk()
+         if part.get_content_type() == "text/html"),
+        None,
+    )
+    if not html:
+        return ""
+    soup = BeautifulSoup(html, "html.parser")
+    for t in soup(["script", "style", "head", "meta", "link"]):
+        t.decompose()
+    return "\n".join(
+        line.strip() for line in soup.get_text("\n").splitlines() if line.strip()
+    )
+
+def _get_all_dates(start_date: str, end_date: str):
+    start = datetime.strptime(start_date, "%d-%b-%Y")
+    end = datetime.strptime(end_date, "%d-%b-%Y")
+    delta = (end - start).days + 1
+    return [(start + timedelta(days=i)).strftime("%Y-%m-%d") for i in range(delta)]
+
+
+
+
+def _extract_with_llm(email_number, subject, body, email_date, email_time):
+    current_email = {
+        "subject": subject,
+        "body": body
+    }
+
+    prompt = f"""
+You are given a Swiggy order confirmation email with a subject and body.
+
+Extract and return only the following:
+- "restaurant_name": name of the restaurant
+- "delivery_address": the delivery address
+- "items": a list of ordered items, each with "name", "quantity", and "price" (number)
+- "total_price": the total bill paid including taxes, charges, etc.
+
+Example output format:
+{{
+  "restaurant_name": "Dominos Pizza",
+  "delivery_address": "123 Main St, City",
+  "total_price": 567,
+  "items": [
+    {{ "name": "Veg Pizza", "quantity": 2, "price": 199 }},
+    {{ "name": "Coke", "quantity": 1, "price": 45 }}
+  ]
+}}
+
+Return only valid JSON. No extra text or comments.
+
+{json.dumps(current_email, indent=2)}
+"""
+
+
+    try:
+        rsp = client.chat.completions.create(
+            model="gpt-4o-mini",
+            temperature=0,
+            messages=[
+                {"role": "system", "content": "You are a precise JSON extractor."},
+                {"role": "user", "content": prompt},
+            ],
+        )
+
+        # Attempt to parse the returned content
+        parsed_data = json.loads(rsp.choices[0].message.content)
+
+        # Wrap into final structure
+        final_output = {
+            "email_number": email_number,
+            "order_date": email_date,
+            "order_time": email_time,
+            "restaurant_name": parsed_data.get("restaurant_name", ""),
+            "delivery_address": parsed_data.get("delivery_address", ""),
+            "items": parsed_data.get("items", []),
+            "total_price": parsed_data.get("total_price", 0)
+        }
+
+        
+        return final_output
+
+    except json.JSONDecodeError as json_err:
+        return {
+            "email_number": email_number,
+            "error": f"JSON decoding failed: {str(json_err)}",
+            "raw_response": rsp.choices[0].message.content if 'rsp' in locals() else None
+        }
+
+    except Exception as e:
+        return {
+            "email_number": email_number,
+            "error": f"Unexpected error: {str(e)}"
+        }
+
+
+
+def fetch_swiggy_orders(start_date: str, end_date: str) -> list[dict]:
+    mail = _imap_connect()
+    all_dates = _get_all_dates(start_date, end_date)
+    orders = []
+
+    for date_str in all_dates:
+        # 1) Try loading from DB
+        day_orders = get_orders_by_date_from_db(date_str)
+        if day_orders:
+            print(f"{date_str} loaded from DB")
+            orders.extend(day_orders)
+            continue
+
+        # 2) Otherwise scrape emails for that date
+        print(f"Fetching Swiggy emails for {date_str}")
+        dt_obj = datetime.strptime(date_str, "%Y-%m-%d")
+        next_day = (dt_obj + timedelta(days=1)).strftime("%d-%b-%Y")
+        this_day = dt_obj.strftime("%d-%b-%Y")
+
+        crit = f'(FROM "[email protected]") SINCE "{this_day}" BEFORE "{next_day}"'
+        _, data = mail.search(None, crit)
+        ids = data[0].split()
+
+        scraped_orders = []
+        for idx, eid in enumerate(ids, 1):
+            _, msg_data = mail.fetch(eid, "(RFC822)")
+            msg = message_from_bytes(msg_data[0][1])
+            subject = msg.get("Subject", "")
+            body_text = _email_to_clean_text(msg)
+
+            try:
+                dt_obj = parsedate_to_datetime(msg["Date"]).astimezone(ZoneInfo("Asia/Kolkata"))
+                email_date = dt_obj.strftime("%d-%b-%Y")
+                email_time = dt_obj.strftime("%H:%M:%S")
+
+                order = _extract_with_llm(idx, subject, body_text, email_date, email_time)
+                scraped_orders.append(order)
+            except Exception as exc:
+                scraped_orders.append({"email_number": idx, "error": str(exc)})
+
+        # 3) Save newly scraped data to DB
+        save_orders_to_db(date_str, scraped_orders)
+        orders.extend(scraped_orders)
+
+    mail.logout()
+    return orders