SYSTEM ACTIVE
Home›MCPs›MCP AWS Server

MCP AWS Server

Community

74·Adequate

Overall Trust Score

MCP server enabling AI models to interact with AWS cloud services including S3, EC2, Lambda, and more. Supports infrastructure management, resource provisioning, and cloud automation through the Model Context Protocol. Extremely powerful but poses critical security risks requiring strict controls.

aws
cloud
mcp
model-context-protocol
Version: 1.0.0
Last Evaluated: November 8, 2025
Official Website →

Trust Vector

Performance & Reliability

85
api reliability
92
Methodology
API uptime and reliability analysis
Evidence
AWS Service Level Agreement
AWS APIs have 99.99% uptime SLA for most services
Date: 2025-11-16
Confidence: highLast verified: 2025-11-08
operation success rate
88
Methodology
Operation success testing
Evidence
AWS SDK
High success rates for API operations with proper retry logic
Date: 2025-11-16
Confidence: highLast verified: 2025-11-08
multi service integration
82
Methodology
Service integration testing
Evidence
AWS Service Integration
Supports multiple AWS services but integration complexity varies
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-08
response time
80
Methodology
API latency testing
Evidence
AWS API Performance
Response times vary by service and region (100ms-2s typical)
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-08
error handling
84
Methodology
Error handling testing
Evidence
AWS Error Handling
Comprehensive error codes with automatic retry mechanisms
Date: 2025-11-16
Confidence: highLast verified: 2025-11-08

Security

64
iam security
78
Methodology
IAM security review
Evidence
AWS IAM
Granular IAM permissions available but AI can use all granted permissions
Date: 2025-11-16
Confidence: highLast verified: 2025-11-08
credential exposure risk
60
Methodology
Credential security analysis
Evidence
AWS Credentials
Access keys stored locally but AI can perform any action within permissions
Date: 2025-11-16
Confidence: highLast verified: 2025-11-08
resource modification risk
52
Methodology
Resource control risk assessment
Evidence
Security Analysis
AI can create, modify, delete AWS resources including EC2, S3, databases
Date: 2025-11-16
Confidence: highLast verified: 2025-11-08
cost control risk
55
Methodology
Cost control assessment
Evidence
AWS Billing
AI can provision expensive resources without built-in cost controls
Date: 2025-11-16
Confidence: highLast verified: 2025-11-08
audit logging
85
Methodology
Audit capabilities review
Evidence
AWS CloudTrail
Comprehensive audit logging via CloudTrail for all API actions
Date: 2025-11-16
Confidence: highLast verified: 2025-11-08
data exfiltration risk
58
Methodology
Data exposure analysis
Evidence
S3 Access
AI can read S3 buckets and database contents, sending data to LLM
Date: 2025-11-16
Confidence: highLast verified: 2025-11-08

Privacy & Compliance

66
data exposure
58
Methodology
Data exposure analysis
Evidence
Data Flow Analysis
AWS resource data and content sent to LLM provider for processing
Date: 2025-11-16
Confidence: highLast verified: 2025-11-08
pii protection
60
Methodology
Privacy controls assessment
Evidence
MCP Security Guidelines
No built-in PII detection when accessing S3, RDS, or other data stores
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-08
vpc isolation
75
Methodology
Network isolation assessment
Evidence
AWS VPC
Can leverage VPC for network isolation but data still sent to LLM
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-08
compliance readiness
68
Methodology
Compliance framework review
Evidence
AWS Compliance
AWS is compliant but sharing data with LLM provider affects compliance
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-08
encryption support
72
Methodology
Encryption capabilities review
Evidence
AWS Encryption
Supports AWS KMS but data decrypted before sending to LLM
Date: 2025-11-16
Confidence: highLast verified: 2025-11-08

Trust & Transparency

80
documentation quality
88
Methodology
Documentation completeness review
Evidence
AWS Documentation
Comprehensive AWS SDK and service documentation
Date: 2025-11-16
Confidence: highLast verified: 2025-11-08
action visibility
85
Methodology
Action traceability assessment
Evidence
CloudTrail Logging
All AWS API actions logged in CloudTrail
Date: 2025-11-16
Confidence: highLast verified: 2025-11-08
mcp implementation
72
Methodology
Implementation documentation review
Evidence
Community Implementation
Community-maintained with variable documentation
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-08
security guidance
75
Methodology
Security documentation review
Evidence
AWS Security Best Practices
AWS provides security guidance but specific MCP guidance limited
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-08

Operational Excellence

77
ease of setup
70
Methodology
Setup complexity assessment
Evidence
AWS SDK Setup
Requires AWS account, IAM configuration, and credential management
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-08
api coverage
85
Methodology
API coverage assessment
Evidence
AWS Services
Supports major AWS services (S3, EC2, Lambda, RDS, etc.)
Date: 2025-11-16
Confidence: highLast verified: 2025-11-08
reliability
82
Methodology
Uptime analysis
Evidence
AWS Status
High reliability with 99.99% uptime for most services
Date: 2025-11-16
Confidence: highLast verified: 2025-11-08
cost predictability
65
Methodology
Cost predictability analysis
Evidence
AWS Pricing
Complex pricing model; AI can incur unexpected costs
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-08
community support
75
Methodology
Community activity analysis
Evidence
Community
Growing community for MCP AWS integration
Date: 2025-11-16
Confidence: mediumLast verified: 2025-11-08

✨ Strengths

  • •Comprehensive access to AWS cloud services and infrastructure
  • •Built on highly reliable AWS infrastructure (99.99% uptime)
  • •Powerful automation capabilities for cloud operations
  • •Excellent audit logging through CloudTrail
  • •Granular IAM permissions for access control
  • •Supports major AWS services (S3, EC2, Lambda, RDS, DynamoDB)

⚠️ Limitations

  • •CRITICAL SECURITY RISK: AI can create, modify, delete infrastructure
  • •Cost control risk - AI can provision expensive resources
  • •Data in S3, RDS, and other services exposed to LLM provider
  • •No built-in PII detection or sensitive data filtering
  • •Complex IAM setup required for secure operation
  • •Potential for catastrophic infrastructure changes if misconfigured

📊 Metadata

license: Varies (AWS SDK Apache 2.0, MCP implementation varies)
supported platforms:
0: All platforms with Node.js/Python
programming languages:
0: TypeScript
1: JavaScript
2: Python
mcp version: 1.0
aws sdk version: v3
supported services:
0: S3
1: EC2
2: Lambda
3: RDS
4: DynamoDB
5: CloudWatch
6: IAM
authentication: AWS Access Keys or IAM Roles
first release: 2024-11
maintained by: Community

Use Case Ratings

code generation

80

Useful for generating infrastructure as code and automation scripts

customer support

68

Can manage support infrastructure but limited direct customer impact

content creation

70

Can manage S3-based content storage but not primary use case

data analysis

85

Excellent for analyzing data in S3, RDS, and other AWS data services

research assistant

78

Good for managing research data in AWS but data exposure concerns

legal compliance

50

Very high risk - can expose confidential data and modify critical infrastructure

healthcare

45

Extreme risk for PHI exposure; HIPAA compliance nearly impossible with LLM sharing

financial analysis

55

High risk for sensitive financial data and infrastructure

education

75

Useful for managing educational infrastructure and resources

creative writing

65

Can manage content storage but significant risk/benefit mismatch