{"id":27111848,"url":"https://github.com/reddy-sh/mcp-hub","last_synced_at":"2026-02-18T00:03:25.230Z","repository":{"id":286518435,"uuid":"961635488","full_name":"reddy-sh/mcp-hub","owner":"reddy-sh","description":"MCP Hub is a comprehensive framework for building, managing, and deploying Model Context Protocol (MCP) clients and servers. 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It leverages the `uv` tool for fast package installation and configuration management.\n\n## Why Use UV?\nUV simplifies package management and configuration with blazing-fast commands. Learn a few commands to get started, and you're good to go:\n\n- Initialize a project:\n  ```bash\n  uv init\n  ```\n- Sync Python version and dependencies:\n  ```bash\n  uv sync\n  ```\n\nFor more details, visit the [UV GitHub repository](https://github.com/astral-sh/uv).\n\n## Motivation\nTo understand the basics of MCP and get started with creating MCP servers, refer to the [MCP Quickstart Server Guide](https://modelcontextprotocol.io/quickstart/server).\n\n## Getting Started\n\n### How to Create a Sample MCP Server\n\n1. **Create a New Project Directory**\n   ```bash\n   uv init XYZ\n   cd XYZ\n   ```\n\n2. **Set Up a Virtual Environment**\n   ```bash\n   uv venv\n   source .venv/bin/activate\n   ```\n\n3. **Install Dependencies**\n   ```bash\n   uv add \"mcp[cli]\" httpx\n   ```\n\n4. **Create the Server File**\n   ```bash\n   touch XYZ.py\n   ```\n\n### How to Run the MCP Server\nTo run the server, use the following command:\n```bash\nuv run XYZ.py\n```\n\n## Example: Creating a New XYZ Server\n\nFollow the steps outlined above to create and run a new XYZ server. Replace `XYZ` with your desired project name.\n\n## Recent Updates\n\n### Notebooks Directory\nThe `notebooks/` directory has been added to the project. It includes configuration files and scripts for setting up and running JupyterHub. Key files include:\n- `jupyterhub_config.py`: Configuration for JupyterHub.\n- `start_jupyterhub.sh`: Script to start the JupyterHub server.\n\n### CIFAR-10 Dataset Downloader\nA new script has been added under `ai/computer-vision/09_datasets/` to download the CIFAR-10 dataset using TensorFlow/Keras. To use it, run:\n```bash\npython ai/computer-vision/09_datasets/download_cifar10.py\n```\nThis script downloads the dataset and prints a confirmation message.\n\n## AI Folder\n\nThe `ai/` folder contains various subdirectories and scripts related to computer vision and artificial intelligence. Below is an overview of its structure and contents:\n\n### Subdirectories and Files\n\n#### 01_image_handling\n- `basic_manipulations.py`: Basic image manipulation techniques.\n- `blue_image.png`: Sample image for testing.\n- `hello_cv.py`: A simple script to demonstrate computer vision basics.\n- `image_representation.py`: Explains image representation in computer vision.\n- `read_display_save.py`: Script to read, display, and save images.\n- `README.md`: Documentation for this subdirectory.\n\n#### 02_image_preprocessing\n- `augmentation.py`: Image augmentation techniques.\n- `normalization.py`: Image normalization methods.\n\n#### 03_feature_extraction\n- `hog_extraction.py`: Extracts Histogram of Oriented Gradients (HOG) features.\n- `sift_surf_extraction.py`: Demonstrates SIFT and SURF feature extraction.\n\n#### 04_basic_ml_concepts\n- `hog_svm_classifier.py`: Implements a classifier using HOG features and SVM.\n\n#### 05_deep_learning_cnn\n- `cnn_architecture.py`: Defines a Convolutional Neural Network (CNN) architecture.\n\n#### 06_image_classification\n- `train_classifier.py`: Script to train an image classifier.\n\n#### 07_object_detection\n- `basic_object_detection.py`: Demonstrates basic object detection techniques.\n\n#### 08_image_segmentation\n- `basic_segmentation.py`: Explains basic image segmentation methods.\n\n#### 09_datasets\n- `download_cifar10.py`: Script to download the CIFAR-10 dataset.\n\n#### 10_utils\n- `image_utils.py`: Utility functions for image processing.\n\n### Additional Files\n- `main.py`: Entry point for AI-related scripts.\n- `pyproject.toml`: Configuration file for the project.\n- `README.md`: Documentation for the `ai/` folder.\n- `run.sh`: Shell script to execute AI-related tasks.\n- `uv.lock`: Lock file for dependencies.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Freddy-sh%2Fmcp-hub","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Freddy-sh%2Fmcp-hub","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Freddy-sh%2Fmcp-hub/lists"}