### MCP Server Setup Checklist Example

Source: https://github.com/awslabs/mcp/blob/main/src/aws-transform-mcp-server/TROUBLESHOOTING.md

A checklist format for reporting MCP server setup findings. This example shows a missing MCP configuration.

```text
MCP Server Setup Check:
✅ Python 3.12 installed
✅ uvx available
✅ AWS credentials valid (account: 123456789)
❌ MCP config missing — no entry found

Would you like me to create the config file for you? I will add the AWS Transform MCP Server entry to <config path>. [Yes / No]
```

--------------------------------

### Start with Petstore API Example

Source: https://github.com/awslabs/mcp/blob/main/src/openapi-mcp-server/README.md

Initiates the MCP server using the Petstore API example. Requires specifying the API name, URL, and OpenAPI specification URL.

```bash
# Start with Petstore API example
awslabs.openapi-mcp-server --api-name petstore --api-url https://petstore3.swagger.io/api/v3 --spec-url https://petstore3.swagger.io/api/v3/openapi.json
```

--------------------------------

### Example Output of Aurora Setup

Source: https://github.com/awslabs/mcp/blob/main/src/aws-api-mcp-server/awslabs/aws_api_mcp_server/core/agent_scripts/registry/create_amazon_aurora_db_cluster_with_instances.script.md

This is an example of the output provided after successfully creating an Aurora cluster and instance.

```text
Aurora cluster 'my-aurora-cluster' created successfully
Aurora instance 'my-aurora-instance-1' created and attached to cluster
Cluster endpoint: my-aurora-cluster.cluster-xyz.us-east-1.rds.amazonaws.com:3306
Database name: myapp
Master username: admin
Password: Managed in AWS Secrets Manager (secret: aurora-master-password)
```

--------------------------------

### Setup HealthImaging MCP Server with uv

Source: https://github.com/awslabs/mcp/blob/main/src/healthimaging-mcp-server/README.md

Recommended setup using uv for installing development dependencies. Ensure you have uv installed and then sync dependencies.

```bash
git clone <repository-url>
cd healthimaging-mcp-server
uv sync --dev
source .venv/bin/activate  # On Windows: .venv\Scripts\activate
```

--------------------------------

### Example Input for Aurora Setup

Source: https://github.com/awslabs/mcp/blob/main/src/aws-api-mcp-server/awslabs/aws_api_mcp_server/core/agent_scripts/registry/create_amazon_aurora_db_cluster_with_instances.script.md

This is an example of the input configuration required for setting up an Aurora cluster and instance.

```yaml
cluster_identifier: my-aurora-cluster
instance_identifier: my-aurora-instance-1
engine: aurora-mysql
instance_class: db.r6g.large
master_username: admin
secret_name: aurora-master-password
database_name: myapp
```

--------------------------------

### Initialize Development Environment

Source: https://github.com/awslabs/mcp/blob/main/src/aws-healthomics-mcp-server/MCP_INSPECTOR_SETUP.md

Perform one-time setup and start the inspector for source code testing.

```bash
cd src/aws-healthomics-mcp-server
uv sync
```

```bash
source .env
npx @modelcontextprotocol/inspector uv run python awslabs/aws_healthomics_mcp_server/server.py
```

--------------------------------

### Setup Virtual Environment

Source: https://github.com/awslabs/mcp/blob/main/src/ecs-mcp-server/DEVELOPMENT.md

Commands to initialize a virtual environment and install development dependencies.

```bash
# Create and activate a virtual environment using uv
cd src/ecs-mcp-server
uv venv
source .venv/bin/activate  # On Unix/macOS
.venv\Scripts\activate     # On Windows

# Install development dependencies
uv pip install -e ".[dev]"
```

--------------------------------

### Development Environment Setup

Source: https://github.com/awslabs/mcp/blob/main/src/aws-healthomics-mcp-server/tests/TESTING_FRAMEWORK.md

Commands to clone the repository and install development dependencies using pip or uv.

```bash
# Clone the repository (if not already done)
git clone <repository-url>
cd src/aws-healthomics-mcp-server

# Install in development mode with test dependencies
pip install -e ".[dev]"

# Or using uv
uv pip install -e ".[dev]"
```

--------------------------------

### Clone Repository and Install Dependencies

Source: https://github.com/awslabs/mcp/blob/main/src/document-loader-mcp-server/README.md

Clone the repository and install dependencies using uv. This setup is for development purposes.

```bash
# Clone the repository
git clone https://github.com/awslabs/mcp.git
cd mcp/src/document-loader-mcp-server

# Install dependencies
uv sync

# Install in development mode
uv pip install -e .
```

--------------------------------

### Quick Start Test Commands

Source: https://github.com/awslabs/mcp/blob/main/src/aws-healthomics-mcp-server/tests/TESTING_FRAMEWORK.md

Commands to install dependencies and execute various test suites within the project directory.

```bash
# Navigate to the project directory
cd src/aws-healthomics-mcp-server

# Install dependencies (if not already installed)
pip install -e .

# Run all tests
python -m pytest tests/ -v

# Run with coverage
python -m pytest tests/ --cov=awslabs.aws_healthomics_mcp_server --cov-report=html

# Run specific test categories
python -m pytest tests/test_models.py -v                    # Model tests
python -m pytest tests/test_workflow_*.py -v               # Workflow tests
python -m pytest tests/test_genomics_*_working.py -v       # Integration tests
```

--------------------------------

### Install OpenAPI MCP Server with All Optional Dependencies

Source: https://github.com/awslabs/mcp/blob/main/src/openapi-mcp-server/README.md

Install the server with all available optional dependencies. This is a convenient option for comprehensive setup.

```bash
# For all optional dependencies
pip install "awslabs.openapi-mcp-server[all]"
```

--------------------------------

### Directories WITH Connectors Structure

Source: https://github.com/awslabs/mcp/blob/main/src/aurora-dsql-mcp-server/kiro_power/steering/language.md

Illustrates the directory structure for projects that include DSQL connectors, emphasizing the preferred example file.

```bash
<language>/<driver>/
├── README.md
├── <config files>
├── src/
│   ├── example_preferred.<ext>           # Synced from connector (pool concurrent if available)
│   ├── alternatives/
│   │   ├── no_connection_pool/
│   │   │   ├── example_with_no_connector.<ext>        # SDK-based, samples-only
│   │   │   └── example_with_no_connection_pool.<ext>  # Synced from connector
│   │   └── pool/
│   │       └── <other pool variants>     # Synced from connector
│   └── <config and util files>
└── test/                                 # Matching test directory layout for all examples

```

--------------------------------

### Install YAML Support and Use YAML Specification

Source: https://github.com/awslabs/mcp/blob/main/src/openapi-mcp-server/README.md

Installs the necessary package for YAML support and then uses a local YAML OpenAPI specification file to start the MCP server.

```bash
# Use a YAML OpenAPI specification file (requires pyyaml)
pip install "awslabs.openapi-mcp-server[yaml]"
awslabs.openapi-mcp-server --spec-path ./openapi.yaml
```

--------------------------------

### Setup and Run Tests

Source: https://github.com/awslabs/mcp/blob/main/src/valkey-mcp-server/README.md

Installs dependencies, activates the virtual environment, and runs unit, live integration, or type-checking tests using uv and pytest.

```bash
uv venv && source .venv/bin/activate && uv sync

# Unit tests
uv run --frozen pytest tests/ -m "not live and not integration"

# Live integration tests (requires VALKEY_HOST and EMBEDDING_PROVIDER)
uv run --frozen pytest tests/test_search_live.py -m live -v

# Type checking
uv run --frozen pyright
```

--------------------------------

### Local Development Setup with pip/venv

Source: https://github.com/awslabs/mcp/blob/main/src/healthlake-mcp-server/README.md

Clone the repository and set up the development environment using pip and venv. Includes virtual environment creation and dependency installation.

```bash
git clone <repository-url>
cd healthlake-mcp-server

# Create virtual environment
python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

# Install dependencies
pip install -e ".[dev]"
```

--------------------------------

### Local Development Setup with conda

Source: https://github.com/awslabs/mcp/blob/main/src/healthlake-mcp-server/README.md

Clone the repository and set up the development environment using conda. Includes environment creation and dependency installation.

```bash
git clone <repository-url>
cd healthlake-mcp-server

# Create conda environment
conda create -n healthlake-mcp python=3.10
conda activate healthlake-mcp

# Install dependencies
pip install -e ".[dev]"
```

--------------------------------

### Clone and Install from Source

Source: https://github.com/awslabs/mcp/blob/main/src/amazon-keyspaces-mcp-server/README.md

Commands to clone the repository, set up a virtual environment, and install the package locally.

```bash
git clone https://github.com/awslabs/mcp.git
cd mcp/src/amazon-keyspaces-mcp-server
```

```bash
python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate
```

```bash
pip install -e .
```

--------------------------------

### Initialize environment configuration

Source: https://github.com/awslabs/mcp/blob/main/src/billing-cost-management-mcp-server/tests/README.md

Create a local .env file from the provided example template.

```bash
cp .env.example .env
```

--------------------------------

### Start MCP Inspector with Installed Package

Source: https://github.com/awslabs/mcp/blob/main/src/aws-healthomics-mcp-server/MCP_INSPECTOR_SETUP.md

Starts the MCP Inspector using the globally installed AWS HealthOmics MCP server package. Ensure environment variables are set.

```bash
npx @modelcontextprotocol/inspector uvx awslabs.aws-healthomics-mcp-server
```

--------------------------------

### DSQL asyncpg preferred example (Python)

Source: https://github.com/awslabs/mcp/blob/main/src/aurora-dsql-mcp-server/kiro_power/steering/language.md

Example of using the DSQL Python Connector with asyncpg.

```python
import aurora_dsql_asyncpg as dsql

# Example usage would go here, referencing the linked GitHub example.
```

--------------------------------

### DSQL psycopg2 preferred example (Python)

Source: https://github.com/awslabs/mcp/blob/main/src/aurora-dsql-mcp-server/kiro_power/steering/language.md

Example of using the DSQL Python Connector with psycopg2.

```python
import aurora_dsql_psycopg2 as dsql

# Example usage would go here, referencing the linked GitHub example.
```

--------------------------------

### Navigate and copy .env.example

Source: https://github.com/awslabs/mcp/blob/main/samples/mcp-integration-with-nova-canvas/README.md

Navigate to the sample directory and copy the .env.example file to .env to add your AWS credentials.

```bash
cd mcp/samples/mcp-integration-with-nova-canvas
cp .env.example .env
```

--------------------------------

### DSQL psycopg preferred example (Python)

Source: https://github.com/awslabs/mcp/blob/main/src/aurora-dsql-mcp-server/kiro_power/steering/language.md

Example of using the DSQL Python Connector with psycopg.

```python
import aurora_dsql_psycopg as dsql

# Example usage would go here, referencing the linked GitHub example.
```

--------------------------------

### Local Development Setup with uv

Source: https://github.com/awslabs/mcp/blob/main/src/healthlake-mcp-server/README.md

Clone the repository and set up the development environment using uv for dependency management. Includes virtual environment activation.

```bash
git clone <repository-url>
cd healthlake-mcp-server
uv sync --dev
source .venv/bin/activate  # On Windows: .venv\Scripts\activate
```

--------------------------------

### Install via UVX

Source: https://github.com/awslabs/mcp/blob/main/src/aws-iot-sitewise-mcp-server/README.md

Recommended installation method using UV to manage the server as a global tool.

```bash
# Install UV if you don't have it yet
curl -sSf https://astral.sh/uv/install.sh | sh

# Clone the repository
git clone https://github.com/awslabs/mcp.git
cd mcp/src/aws-iot-sitewise-mcp-server

# Install as a uv tool (this makes it available globally via uvx)
uv tool install .

# The server is now available globally via uvx
uvx awslabs.aws-iot-sitewise-mcp-server
# use @latest flag for automatically pull updates on server
uvx awslabs.aws-iot-sitewise-mcp-server@latest

# Note: The server runs silently, waiting for MCP client connections.
# You'll need to configure an MCP client to connect to it.
```

--------------------------------

### Set Up Virtual Environment

Source: https://github.com/awslabs/mcp/blob/main/src/healthlake-mcp-server/CONTRIBUTING.md

Synchronize development dependencies and activate the virtual environment.

```bash
uv sync --dev
source .venv/bin/activate  # On Windows: .venv\Scripts\activate
```

--------------------------------

### Prerequisites Check

Source: https://github.com/awslabs/mcp/blob/main/src/aurora-dsql-mcp-server/kiro_power/steering/mcp-setup.md

Command to check if 'uv' is installed, a prerequisite for MCP server setup.

```bash
uv --version
```

--------------------------------

### Valkey MCP Server Example Usage Commands

Source: https://github.com/awslabs/mcp/blob/main/src/valkey-mcp-server/README.md

A list of example commands for creating search indexes, adding documents, performing searches, and managing JSON configurations with TTL.

```text
"Create a search index for product data with title, category, price, and embedding fields"
```

```text
"Add these product documents and generate embeddings from the title field"
```

```text
"Search for products similar to 'wireless headphones'"
```

```text
"Find products similar to product:123"
```

```text
"Show me the average price by category"
```

```text
"Store this JSON config and set a 1-hour TTL"
```

```text
"Get the nested value at $.settings.theme from the config key"
```

--------------------------------

### DSQL pgx preferred example (Go)

Source: https://github.com/awslabs/mcp/blob/main/src/aurora-dsql-mcp-server/kiro_power/steering/language.md

Example of using the DSQL Go Connector with pgx for automatic IAM auth.

```go
import "github.com/awslabs/aurora-dsql-connectors/go/pgx/dsql"

// Example usage would go here, referencing the linked GitHub example.
```

--------------------------------

### Go pgx Import

Source: https://github.com/awslabs/mcp/blob/main/src/aurora-dsql-mcp-server/skills/dsql-skill/references/language.md

Example of importing the DSQL pgx connector for Go.

```go
import aurora-dsql-connectors/go/pgx/dsql
```

--------------------------------

### Python asyncpg Import

Source: https://github.com/awslabs/mcp/blob/main/src/aurora-dsql-mcp-server/skills/dsql-skill/references/language.md

Example of importing the DSQL asyncpg connector for Python.

```python
import aurora_dsql_asyncpg as dsql
```

--------------------------------

### Install and run with uvx

Source: https://github.com/awslabs/mcp/blob/main/src/healthlake-mcp-server/README.md

Recommended method to install and execute the latest version of the server automatically.

```bash
uvx awslabs.healthlake-mcp-server@latest
```

--------------------------------

### Python psycopg2 Import

Source: https://github.com/awslabs/mcp/blob/main/src/aurora-dsql-mcp-server/skills/dsql-skill/references/language.md

Example of importing the DSQL psycopg2 connector for Python.

```python
import aurora_dsql_psycopg2 as dsql
```

--------------------------------

### Create Database Example

Source: https://github.com/awslabs/mcp/blob/main/src/mysql-mcp-server/kiro_power/steering/aurora-mysql.md

Standard SQL command to create a new database.

```sql
CREATE DATABASE mydb;
```

--------------------------------

### Python psycopg Import

Source: https://github.com/awslabs/mcp/blob/main/src/aurora-dsql-mcp-server/skills/dsql-skill/references/language.md

Example of importing the DSQL psycopg connector for Python.

```python
import aurora_dsql_psycopg as dsql
```

--------------------------------

### Create Virtual Environment and Install Dependencies (Traditional)

Source: https://github.com/awslabs/mcp/blob/main/src/aws-iot-sitewise-mcp-server/DEVELOPMENT.md

Set up a traditional UV development environment by creating a virtual environment and installing the project with its development dependencies.

```bash
uv venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate
uv pip install -e ".[dev]"
```

--------------------------------

### Check if Claude CLI is installed

Source: https://github.com/awslabs/mcp/blob/main/src/aurora-dsql-mcp-server/skills/dsql-skill/mcp/platforms/claude-code.md

Command to check if the Claude CLI is installed on the system.

```bash
claude --version
```

--------------------------------

### Install and run with uv

Source: https://github.com/awslabs/mcp/blob/main/src/healthlake-mcp-server/README.md

Alternative installation method using the uv tool.

```bash
uv tool install awslabs.healthlake-mcp-server
awslabs.healthlake-mcp-server
```

--------------------------------

### Quick Start Installation

Source: https://github.com/awslabs/mcp/blob/main/src/aws-transform-mcp-server/README.md

Installs the AWS Transform MCP Server using uvx.

```bash
uvx awslabs.aws-transform-mcp-server@latest
```

--------------------------------

### Full CDK Deployment Example

Source: https://github.com/awslabs/mcp/blob/main/src/dynamodb-mcp-server/awslabs/dynamodb_mcp_server/cdk_generator/templates/README.md

An example demonstrating the complete process of setting AWS profile and region, bootstrapping the CDK with a specific account and region, deploying the stack, and then destroying it.

```bash
export AWS_PROFILE=my-profile
export AWS_REGION=us-west-2

npx cdk bootstrap aws://123456789012/us-west-2

npx cdk deploy

npx cdk destroy
```

--------------------------------

### Development Setup Commands

Source: https://github.com/awslabs/mcp/blob/main/src/aws-healthomics-mcp-server/README.md

Commands to initialize the development environment.

```bash
git clone <repository-url>
cd aws-healthomics-mcp-server
uv sync
```

--------------------------------

### Rust SQLx After Connect Hook

Source: https://github.com/awslabs/mcp/blob/main/src/aurora-dsql-mcp-server/kiro_power/steering/language.md

Example of using the `after_connect` hook in SQLx to set the search path.

```rust
.after_connect(|conn, _| conn.execute("SET search_path = public"))
```

--------------------------------

### Example AI IDE Queries

Source: https://github.com/awslabs/mcp/blob/main/src/valkey-mcp-server/README.md

Demonstrates sample queries for interacting with the Valkey MCP server in an AI IDE, covering index creation, document addition, search, and aggregation.

```text
"Create a search index called products with title (TEXT), category (TAG), and price (NUMERIC) fields"
```

```text
"Add 3 product documents to the products index"
```

```text
"Search for electronics in the products index"
```

```text
"Show me the average price by category"
```

--------------------------------

### node-postgres (pg) Example

Source: https://github.com/awslabs/mcp/blob/main/src/aurora-dsql-mcp-server/kiro_power/steering/language.md

Recommended approach for node-postgres with automatic IAM authentication using the DSQL Node.js Connector.

```javascript
import { AuroraNodePostgresConnector } from "@aws/aurora-dsql-node-postgres-connector";

const connector = new AuroraNodePostgresConnector({
  // Your Aurora DSQL cluster endpoint
  host: "your-dsql-cluster-endpoint.aws-dsql.amazonaws.com",
  port: 5432,
  database: "postgres",
  // The connector automatically handles IAM authentication
});

// Use the connector like a standard pg.Pool
const pool = connector.createPool();

// Example query
const result = await pool.query("SELECT 1");
console.log(result.rows);

```

--------------------------------

### Navigate and Copy Environment File

Source: https://github.com/awslabs/mcp/blob/main/samples/mcp-integration-with-kb/README.md

Navigate to the sample directory and copy the .env.example file to .env. Remember to add your AWS credentials to the .env file.

```bash
cd mcp/samples/mcp-integration-with-kb
cp .env.example .env
```

--------------------------------

### postgres.js Example

Source: https://github.com/awslabs/mcp/blob/main/src/aurora-dsql-mcp-server/kiro_power/steering/language.md

Lightweight alternative for postgres.js with automatic IAM authentication using the DSQL Node.js Connector, suitable for serverless environments.

```javascript
import postgres from "postgres";
import { AuroraNodePostgresConnector } from "@aws/aurora-dsql-node-postgres-connector";

const connector = new AuroraNodePostgresConnector({
  // Your Aurora DSQL cluster endpoint
  host: "your-dsql-cluster-endpoint.aws-dsql.amazonaws.com",
  port: 5432,
  database: "postgres",
  // The connector automatically handles IAM authentication
});

// Use the connector to get a connection string for postgres.js
const connectionString = connector.getConnectionString();

const db = postgres(connectionString);

// Example query
const result = await db`SELECT 1`;
console.log(result);

```

--------------------------------

### Build and Install Package

Source: https://github.com/awslabs/mcp/blob/main/src/aws-iot-sitewise-mcp-server/DEVELOPMENT.md

Commands for building and installing the project using uv.

```bash
# Build distribution packages
uv build

# Install locally in development mode
uv pip install -e .

# Install from PyPI (if published)
uv pip install awslabs.aws-iot-sitewise-mcp-server
```

--------------------------------

### Clone and Navigate to Repository

Source: https://github.com/awslabs/mcp/blob/main/docusaurus/docs/servers/healthimaging-mcp-server.md

Initializes the local development environment by cloning the source code and entering the project directory.

```bash
git clone https://github.com/awslabs/mcp-server-collection.git
cd mcp-server-collection/src/healthimaging-mcp-server
```

--------------------------------

### Directories WITHOUT Connectors Structure

Source: https://github.com/awslabs/mcp/blob/main/src/aurora-dsql-mcp-server/kiro_power/steering/language.md

Illustrates the directory structure for projects that do not include DSQL connectors, highlighting the main example file.

```bash
<language>/<driver>/
├── README.md
├── <config files>
├── src/
│   ├── example.<ext>
│   └── <config and util files>
└── test/                                 # Matching test directory layout for all examples

```

--------------------------------

### Install via uvx

Source: https://github.com/awslabs/mcp/blob/main/docusaurus/docs/servers/healthimaging-mcp-server.md

Recommended method for running the MCP server directly.

```bash
uvx awslabs.healthimaging-mcp-server@latest
```

--------------------------------

### Start ADOT Collector Service

Source: https://github.com/awslabs/mcp/blob/main/src/cloudwatch-applicationsignals-mcp-server/awslabs/cloudwatch_applicationsignals_mcp_server/enablement_guides/templates/ec2/ec2-java-enablement.md

Starts the ADOT Collector as a systemd service, ensuring it runs in the background and collects telemetry data. This command is executed after the collector is installed and configured.

```bash
sudo systemctl start adot-collector
```

--------------------------------

### Set up Python Virtual Environment and Install Dependencies

Source: https://github.com/awslabs/mcp/blob/main/src/elasticache-mcp-server/README.md

Use 'uv' to create a virtual environment, activate it, synchronize dependencies, and run tests. This ensures a consistent development environment.

```bash
uv venv
source .venv/bin/activate
uv sync
uv run --frozen pytest
```

--------------------------------

### Start Local Development Server

Source: https://github.com/awslabs/mcp/blob/main/docusaurus/README.md

Starts a local development server for live previewing changes. Changes are reflected without server restart.

```bash
npm start
```

--------------------------------

### Create Database

Source: https://github.com/awslabs/mcp/blob/main/src/postgres-mcp-server/kiro_power/steering/aurora-postgres.md

Standard command to initialize a new database.

```sql
CREATE DATABASE mydb;
```

--------------------------------

### cluster-info.sh Usage

Source: https://github.com/awslabs/mcp/blob/main/src/aurora-dsql-mcp-server/skills/dsql-skill/scripts/README.md

Examples of getting detailed information about a specific cluster.

```bash
./scripts/cluster-info.sh abc123def456
./scripts/cluster-info.sh abc123def456 --region us-west-2
```

--------------------------------

### Local Development Setup

Source: https://github.com/awslabs/mcp/blob/main/src/aws-bedrock-custom-model-import-mcp-server/README.md

Steps to set up and run the MCP server locally for development.

```APIDOC
## Local development

To make changes to this MCP locally and run it:

1. Clone this repository:

   ```bash
   git clone https://github.com/awslabs/mcp.git
   cd mcp/src/aws-bedrock-custom-model-import-mcp-server
   ```

2. Install dependencies:

   ```bash
   pip install -e .
   ```

3. Configure AWS credentials:

   - Ensure you have AWS credentials configured in `~/.aws/credentials` or set the appropriate environment variables.
   - You can also set the AWS_PROFILE and AWS_REGION environment variables.

4. Run the server:

   ```bash
   python -m awslabs.aws_bedrock_custom_model_import_mcp_server.server
   ```

5. To use this MCP server with AI clients, add the following to your MCP configuration:

```json
{
  "mcpServers": {
    "awslabs.aws-bedrock-custom-model-import-mcp-server": {
      "command": "mcp/src/aws-bedrock-custom-model-import-mcp-server/bin/awslabs.aws-bedrock-custom-model-import-mcp-server/",
      "env": {
        "AWS_PROFILE": "your-aws-profile",
        "AWS_REGION": "us-east-1",
        "BEDROCK_MODEL_IMPORT_S3_BUCKET": "your-model-bucket",
        "BEDROCK_MODEL_IMPORT_ROLE_ARN": "your-role-arn"
      },
      "disabled": false,
      "autoApprove": []
    }
  }
}
```
```

--------------------------------

### MCP Inspector CLI Command Example

Source: https://github.com/awslabs/mcp/blob/main/src/ecs-mcp-server/tests/integ/mcp-inspector/README.md

Example of how to invoke an ECS troubleshooting tool using the MCP Inspector CLI. Ensure the --config and --server arguments match your setup.

```bash
mcp-inspector \
  --config /tmp/mcp-config.json \
  --server local-ecs-mcp-server \
  --cli \
  --method tools/call \
  --tool-name ecs_troubleshooting_tool \
  --tool-arg "action=detect_image_pull_failures" \
  --tool-arg 'parameters={"cluster_name":"test-cluster"}'
```

--------------------------------

### Setup HealthImaging MCP Server with pip/venv

Source: https://github.com/awslabs/mcp/blob/main/src/healthimaging-mcp-server/README.md

Alternative setup using Python's built-in venv and pip for dependency management. This involves creating a virtual environment and installing the project with development dependencies.

```bash
git clone <repository-url>
cd healthimaging-mcp-server

# Create virtual environment
python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

# Install dependencies
pip install -e ".[dev]"
```

--------------------------------

### Install via Pip

Source: https://github.com/awslabs/mcp/blob/main/src/aws-iot-sitewise-mcp-server/README.md

Alternative installation method using pip from PyPI or source.

```bash
# Install from PyPI (when published)
pip install awslabs.aws-iot-sitewise-mcp-server

# Or install from source
git clone https://github.com/awslabs/mcp.git
cd mcp/src/aws-iot-sitewise-mcp-server
pip install .

# Run the server
python -m awslabs.aws_iot_sitewise_mcp_server.server
```

--------------------------------

### Install via uv

Source: https://github.com/awslabs/mcp/blob/main/docusaurus/docs/servers/healthimaging-mcp-server.md

Standard installation method using the uv package manager.

```bash
uv add awslabs.healthimaging-mcp-server
```

--------------------------------

### Define Rules for AI Coding Agents

Source: https://github.com/awslabs/mcp/blob/main/VIBE_CODING_TIPS_TRICKS.md

Example of configuration rules to guide AI agents in code generation and maintenance.

```markdown
- If a file is longer than 300 lines of code, break it down into multiple files.
- Add documentation for every new piece of code added.
```