feat(new MCP client Sample): Sample Implementation for MCP Integration with Nova Canvas (#189)

* Sample Implementation for MCP Integration with Nova Canvas

* Fixing Pre-commit findings

* Bug fix for forcing user to enter mandatory negative prompt to align with MCP Spec.

* chore(build): fix pre commit

---------

Co-authored-by: Alain Krok <[email protected]>

Author: prajwalendra

.gitignore

@@ -555,3 +555,4 @@ dist
 
 
 # End of https://www.toptal.com/developers/gitignore/api/jetbrains+all,pycharm+all,node
+samples/mcp-integration-with-nova-canvas/output/*

samples/mcp-integration-with-nova-canvas/.env.example

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+AWS_PROFILE=<your-aws-profile>
+AWS_REGION=<your-aws-region>

samples/mcp-integration-with-nova-canvas/.python-version

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+3.12

samples/mcp-integration-with-nova-canvas/README.md

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+# MCP Integration with Amazon Nova Canvas
+
+This repository outlines a basic implementation of the [Model Context Protocol](https://modelcontextprotocol.io/) integration with Amazon Nova Canvas for image generation
+
+## Overview
+
+There are two parts to this implementation:
+
+1. The `user_interfaces/image_generator_st.py` file, which handles the Streamlit/User Interface for the image generator
+2. The `client_server.py` file, which handles the MCP client and server implementation
+
+The exact MCP server code leveraged can be found in the [src/nova-canvas-mcp-server](../../src/nova-canvas-mcp-server/) folder.
+
+### Architecture
+
+The implementation follows this flow:
+1. A Streamlit UI provides the user interface for image generation
+2. The UI communicates with a FastAPI server
+3. The FastAPI server uses the MCP client to communicate with the Nova Canvas MCP server
+4. The Nova Canvas MCP server interacts with Amazon Bedrock to generate images
+5. The generated images are returned to the UI for display
+
+## Setup
+
+### Prerequisites
+
+- The [uv](https://docs.astral.sh/uv/getting-started/installation/) package manager
+- AWS Account with Bedrock access and proper IAM permissions - [Getting Started with Amazon Bedrock](https://docs.aws.amazon.com/bedrock/latest/userguide/getting-started.html)
+- Access to the Amazon Nova Canvas and Amazon Nova Micro model (optional for prompt improvement) in Bedrock
+
+### Installation
+
+1. Clone the repository.
+
+```bash
+git clone https://github.com/awslabs/mcp.git
+```
+
+2. Navigate to the sample directory and copy the .env.example file to .env and add your AWS credentials.
+
+```bash
+cd mcp/samples/mcp-integration-with-nova-canvas
+cp .env.example .env
+```
+
+3. Open two different terminals and install the dependencies in each.
+
+```bash
+uv sync
+```
+
+then activate the virtual environment
+
+```bash
+source .venv/bin/activate
+```
+4. In one of the terminals, run the FastAPI server
+
+```bash
+uvicorn clients.client_server:app --reload
+```
+
+5. In the other terminal, run the Streamlit app
+
+```bash
+streamlit run user_interfaces/image_generator_st.py
+```
+
+6. The image generator should now be running on [http://localhost:8501/](http://localhost:8501/)
+
+## Usage
+
+1. Enter a text prompt describing the image you want to generate
+2. Optionally, add a negative prompt to specify what you don't want in the image
+3. Customize image parameters (dimensions, quality, etc.)
+4. For color-guided generation, select colors from the color picker
+5. Click "Generate Image" to create your image
+6. View the generated image and save it if desired
+
+## Troubleshooting
+
+Logs are available in the terminal where you ran the FastAPI server, outlining various steps and actions taken by the server.
+
+If you see an error about `boto3` or `streamlit` not being found, it is likely because you did not activate the virtual environment:
+
+```bash
+uv sync
+source .venv/bin/activate