dileepkumar10/AWS_MCP_Server
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The Model Context Protocol (MCP) server is a framework designed to simplify cloud application deployment using context-aware infrastructure automation with AWS services.
š AWS MCP Server
The Model Context Protocol (MCP) server is a powerful framework designed to simplify cloud application deployment by leveraging context-aware infrastructure automation using native AWS services.
š§ Features
- ā Context-driven deployment (team, env, region)
- āļø Auto-scaling with smart defaults
- āļø Native AWS integration (EC2, Lambda, ECS, RDS, S3, EKS)
- š CI/CD support with CodePipeline, CodeBuild, CodeDeploy
- š° Cost optimization via AWS Cost Explorer
- š IAM & KMS integrated for secure deployments
- š YAML-based manifest system
š¦ Supported AWS Services
š„ļø Compute
- EC2
- Lambda
š¦ Containers
- ECS
- EKS
- ECR
šļø Storage & Databases
- S3
- RDS
š Identity & Security
- IAM
- KMS
- ACM
š§ CI/CD
- CodePipeline
- CodeBuild
- CodeDeploy
- CodeCommit
š Monitoring & Billing
- CloudWatch
- CloudWatch Logs
- Cost Explorer
- Organizations
- Tags & Resource Groups
š§ Why MCP?
Feature | Traditional API | MCP |
---|---|---|
Declarative | ā | ā |
Context-Aware | ā | ā |
Secure by Default | ā | ā |
Cost-Aware | ā | ā |
Pluggable Deployments | ā | ā |
š Get Started
1. Clone the Repo
git clone https://github.com/yourname/aws-mcp-server.git
cd aws-mcp-server
2. Install uv
pip install uv
3. Install Project Requirements
uv pip install -r requirements.txt
4. Install GitHub Copilot Chat
- Open VS Code
- Go to Extensions ā GitHub Copilot Chat ā Install
š„ļø VS Code Configuration
Open VS Code Command Palette with Ctrl+Shift+P
, then:
- Search for:
Preferences: Open User Settings (JSON)
- Paste and edit the following:
{
"mcp": {
"servers": {
"aws": {
"command": "uv",
"args": [
"run",
"--with",
"mcp[cli],boto3",
"mcp",
"run",
"D:\\Dileep\\MCPAws\\awsmcp\\main.py"
]
}
}
},
"files.autoSave": "afterDelay"
}
š Creating a New MCP Server
Step-by-step Guide:
# 1. Install GitHub Copilot Chat Extension (VS Code)
# 2. Install uv package manager
pip install uv
# 3. Initialize a new MCP project
uv init my-first-mcp-server
cd my-first-mcp-server
# 4. Add MCP CLI to your project
uv add "mcp[cli]"
# 5. (Optional) Fix any typer type errors
pip install --upgrade typer
6. Write code in main.py
Example:
from mcp import App, Context
app = App(name="aws-mcp-server")
@app.task()
def deploy(ctx: Context):
print(f"Deploying to {ctx.env} in region {ctx.region}")
7. Update VS Code settings.json
{
"mcp": {
"servers": {
"aws": {
"command": "uv",
"args": [
"run",
"--with",
"mcp[cli],boto3",
"mcp",
"run",
"D:\\Dileep\\MCPAws\\awsmcp\\main.py"
]
}
}
},
"files.autoSave": "afterDelay"
}
š¤ Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
š¬ Contact
Author: R S Dileep kumar š§ Email: kumardileep2462000@gmail.com š LinkedIn: https://linkedin.com/in/r-s-dileep
š·ļø Tags
#AWS #MCP #ModelContextProtocol #DevOps #CloudAutomation
#GitHubCopilot #Python #uv #IaC #CloudNative
MCP makes your AWS deployments smarter, faster, and context-aware. šÆ