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{
  "mcpServers": {
    "mcp-tools": {
      "command": "uv",
      "args": [
        "--directory",
        "C:/Users/Braincore/Documents/GitHub/mcp-tools",
        "run",
        "python",
        "server.py"

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algonacci

Step 1: Data Ingestion

Using Google Cloud Storage to store raw data from multiple sources

from google.cloud import storage
from google.cloud import bigquery

def upload_to_gcs(bucket_name, file_name, data):
    client = storage.Client()

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from ultralytics import YOLO
import os
import cv2

# Load the model
model = YOLO("model.pt")

# Specify the folder containing the images
image_folder = "./images"

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MAPPING = {
    'ا': 'a', 'أ': 'a', 'إ': 'i', 'آ': 'a', 'ب': 'b', 'ت': 't', 'ث': 'th', 'ج': 'j', 'ح': 'h',
    'خ': 'kh', 'د': 'd', 'ذ': 'dh', 'ر': 'r', 'ز': 'z', 'س': 's', 'ش': 'sh', 'ص': 's',
    'ض': 'd', 'ط': 't', 'ظ': 'z', 'ع': "'a", 'غ': 'gh', 'ف': 'f', 'ق': 'q', 'ك': 'k',
    'ل': 'l', 'م': 'm', 'ن': 'n', 'ه': 'h', 'و': 'w', 'ي': 'y', 'ئ': 'y', 'ى': 'a',
    'ة': 'h', 'ؤ': 'w'
}

VOWELS = {
    '\u064E': 'a',  # Fatha

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FROM node:lts-alpine as build-stage
WORKDIR /app
COPY package*.json ./
RUN npm install
COPY . .
RUN npm run build

FROM node:lts-alpine as serve-stage
WORKDIR /app
RUN npm install -g serve

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import psycopg2

def check_tables_in_database(host, port, username, password, database):
    try:
        # Attempt to connect to the PostgreSQL database
        connection = psycopg2.connect(
            host=host,
            port=port,
            user=username,
            password=password,

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import mysql.connector

def check_tables_in_database(host, username, password, database):
    try:
        # Attempt to connect to the MySQL database
        connection = mysql.connector.connect(
            host=host,
            user=username,
            password=password,
            database=database

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import os
from keras.models import load_model
from PIL import Image, ImageOps
import numpy as np

# Load the model
model = load_model("keras_Model.h5", compile=False)

# Load the labels
class_names = open("labels.txt", "r").readlines()

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