AWS MCP Server Engineering (eBook)

Building Secure, Scalable, and Automated Cloud Systems with Modular Command Protocol Integrations

Caden Nexon (Autor)

eBook Download: EPUB

2025 | 1. Auflage
233 Seiten
Publishdrive (Verlag)
9780001119536 (ISBN)

Infos

AWS MCP Server Engineering is the definitive guide for architects, DevOps engineers, and cloud professionals who want to build the next generation of secure, automated, and modular cloud systems using the Modular Command Protocol (MCP) ecosystem.

This book demystifies how MCP servers, clients, and tools integrate seamlessly with AWS to create intelligent, event-driven, and highly maintainable infrastructure. Through clear explanations, best practices, and real-world architectural patterns, you'll learn how to design cloud systems that are scalable, predictable, and deeply automated-without unnecessary complexity.

Inside, you'll discover how to:

Architect AWS-based MCP server ecosystems for high reliability and performance

Implement secure, role-based, and policy-driven cloud automation

Build modular workflows using Lambda, Step Functions, SQS, SNS, API Gateway, and more

Leverage Infrastructure as Code (IaC) with Terraform and AWS CDK to automate everything

Integrate MCP with monitoring, logging, and alerting frameworks for complete observability

Design cloud systems using modern patterns such as event-driven automation, microservices-based command modules, and distributed orchestration

Apply production-ready security, compliance, and cost-optimization techniques

Develop real-world automation pipelines and MCP extensions for CI/CD, governance, and cloud operations

Whether you're modernizing existing systems or building automated cloud environments from scratch, this book equips you with the knowledge and hands-on frameworks to deliver secure, scalable, and future-ready cloud platforms on AWS.

If you want to master MCP-driven cloud automation and engineer cloud systems that truly run themselves, this is the guide you need.

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Implementing a Minimal MCP Server with AWS SDK

The theoretical foundation now transitions to practical implementation. The following example constructs a minimal MCP server using Python 3.11, FastAPI for HTTP handling, Pydantic for schema validation, and boto3 for AWS interactions. This server exposes a single capability group (storage) with two tools: list_buckets and upload_object. The implementation demonstrates manifest generation, schema validation, IAM-based authentication, and S3 integration.

python

1 import uuid

2 import hashlib

3 import json

4 from datetime import datetime, timedelta

5 from typing import Any, Dict, List, Optional

6

7 import boto3

8 from botocore.exceptions import ClientError, BotoCoreError

9 from fastapi import FastAPI, Request, Response, HTTPException, Depends

10 from fastapi.security import HTTPBearer, HTTPAuthorizationCredentials

11 from pydantic import BaseModel, Field, validator

12 from jose import JWTError, jwt

13 import uvicorn

14

15 # AWS clients and configuration

16 s3_client = boto3.client("s3")

17 sts_client = boto3.client("sts")

18

19 # MCP server configuration

20 SERVER_ID = "aws-mcp-demo-01"

21 MANIFEST_VERSION = "1.0.0"

22 JWT_SECRET = "development-secret-change-in-production"

23 JWT_ALGORITHM = "HS256"

24 TOKEN_EXPIRY_MINUTES = 15

25

26 app = FastAPI(title="AWS MCP Demo Server", version=MANIFEST_VERSION)

27 security = HTTPBearer()

28

29

30 class ToolParameter(BaseModel):

31 name: str = Field(..., description="Parameter name")

32 type: str = Field(..., description="JSON type: string, number, boolean, object, array")

33 description: str = Field(..., description="Human readable description")

34 required: bool = Field(True, description="Whether parameter is required")

35 default: Optional[Any] = Field(None, description="Default value if omitted")

36

37 @validator("type")

38 def validate_type(cls, v):

39 valid_types = {"string", "number", "boolean", "object", "array", "integer"}

40 if v not in valid_types:

41 raise ValueError(f"Invalid type: {v}")

42 return v

43

44

45 class ToolSchema(BaseModel):

46 tool_id: str = Field(..., description="Unique namespaced tool identifier")

47 display_name: str = Field(..., description="Human readable name")

48 description: str = Field(..., description="Detailed tool description")

49 parameters: List[ToolParameter] = Field(default_factory=list)

50 output_schema: Dict[str, Any] = Field(default_factory=dict)

51 idempotent: bool = Field(False, description="Supports idempotency keys")

52 streaming: bool = Field(False, description="Supports streaming responses")

53

54

55 class CapabilityGroup(BaseModel):

56 group_id: str = Field(..., description="Unique capability group identifier")

57 display_name: str = Field(..., description="Human readable group name")

58 description: str = Field(..., description="Group purpose and scope")

59 tool_ids: List[str] = Field(default_factory=list)

60

61

62 class MCPManifest(BaseModel):

63 server_id: str

64 version: str

65 timestamp: datetime

66 capabilities: List[CapabilityGroup]

67 tools: List[ToolSchema]

68

69

70 # In-memory storage for demo (use DynamoDB in production)

71 active_subscriptions: Dict[str, Dict] = {}

72 idempotency_store: Dict[str, Dict] = {}

73

74

75 def generate_manifest() -> MCPManifest:

76 return MCPManifest(

77 server_id=SERVER_ID,

78 version=MANIFEST_VERSION,

79 timestamp=datetime.utcnow(),

80 capabilities=[

81 CapabilityGroup(

82 group_id="storage",

83 ...

Produkt-Details

• Erscheint lt. Verlag: 5.12.2025
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Informatik ► Programmiersprachen / -werkzeuge
• ISBN-13: 9780001119536 / 9780001119536