aws-finops-mcp-server and aws-security-mcp

aws-finops-mcp-server
56
Established
aws-security-mcp
38
Emerging
Maintenance 2/25
Adoption 14/25
Maturity 18/25
Community 22/25
Maintenance 2/25
Adoption 9/25
Maturity 9/25
Community 18/25
Stars: 176
Forks: 54
Downloads: 84
Commits (30d): 0
Language: Python
License: MIT
Stars: 81
Forks: 16
Downloads:
Commits (30d): 0
Language: Python
License: Apache-2.0
Stale 6m
Stale 6m No Package No Dependents

About aws-finops-mcp-server

ravikiranvm/aws-finops-mcp-server

An MCP (Model Context Protocol) server that brings powerful AWS FinOps capabilities directly into your AI assistant. Analyze cloud costs, audit for waste, and get budget insights using natural language, all while keeping your credentials secure on your local machine.

Exposes AWS Cost Explorer and Budget APIs through two primary tools—`get_cost` for granular cost queries across services/tags/time ranges, and `run_finops_audit` for detecting infrastructure waste (stopped instances, unattached volumes, orphaned IPs)—while supporting multi-profile and multi-region queries via existing AWS CLI credentials. Implements the MCP stdio transport pattern, integrating natively with Claude Desktop and Amazon Q CLI as MCP clients, requiring only read-only IAM permissions (ce:GetCostAndUsage, budgets:ViewBudget, ec2:Describe*) with all credential handling delegated to local AWS CLI profiles.

About aws-security-mcp

groovyBugify/aws-security-mcp

A Model Context Protocol server that connects AI assistants like Claude to AWS security services, allowing them to autonomously query, inspect, and analyze AWS infrastructure for security issues and misconfigurations.

Integrates with GuardDuty, SecurityHub, and Access Analyzer for unified security findings, while supporting cross-account AWS Organization discovery through STS role assumption. Provides Athena-powered log analysis of CloudTrail and VPC Flow Logs for forensic investigation, and exposes network topology mapping and blast radius analysis alongside natural language querying. Deployable as a local Python service or containerized ECS workload with stdio/HTTP transport for MCP client integration.

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