MCP-AWS-S3Upload

# MCP MoP Uploader ## Purpose This application is built to automate the generation and storage of **Method of Procedure (MoP)** documents using a Large Language Model (LLM) from OpenAI, integrated with **AWS S3** via a custom [Model Context Protocol (MCP)] tool. The goal is to reduce manual effort in creating MoP documents and streamline their delivery to cloud storage systems. --- ## Setup Instructions ### 1. Clone the repository ```bash git clone https://github.com/adhika28/MCP-AWS-S3Upload.git cd MCP-AWS-S3Upload ``` ### 2. Create a virtual environment ```bash python3 -m venv .venv source .venv/bin/activate ``` ### 3. Install dependencies ```bash pip install -r requirements.txt ``` ### 4. Set environment variables You can set them via terminal or create a `.env` file: ```bash export OPENAI_API_KEY="your-openai-api-key" export AWS_ACCESS_KEY_ID="your-aws-access-key-id" export AWS_SECRET_ACCESS_KEY="your-aws-secret-key" export S3_BUCKET="your-s3-bucket-name" ``` --- ## Usage Run the main script: ```bash python run_mop.py ``` You will be prompted to enter a scenario: ``` MoP apa yang ingin kamu buat? provisioning EC2 with Amazon Linux ``` The app will: 1. Generate a MoP document using OpenAI's GPT-4. 2. Save it locally as `Generated_MoP.docx`. 3. Upload the file to `s3://test-mcp-bucket/MoP/Generated_MoP.docx`. --- ## Project Structure ``` . ├── run_mop.py # Main application ├── requirements.txt # Python dependencies ├── mcp/tools/base.py # Simulated MCP toolbase └── examples/tools/s3_uploader.py # Custom S3 uploader tool ``` --- ## imitations and Known Issues - No input validation or prompt quality check is implemented. - Document approval workflow or versioning is **not included**. - S3 permissions must be correctly configured; otherwise, upload will fail with `AccessDenied`. --- ## Future Improvements - Add web UI for user input - Implement version tracking and metadata tagging for MoP files - Add approval flow --- Made with 💻 by Putu