AWS MCP Audit
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 10 tools
The tools have distinct names suggesting different AWS audit functions, but without descriptions, there is potential ambiguity in overlapping areas like cost analysis (cost_explorer_by_region, cost_explorer_by_service, cost_explorer_summary_tool, cost_signals) and snapshot handling (collect_snapshot, get_snapshot_summary). An agent might struggle to choose between similar-sounding tools without clear purpose differentiation.
Most tools follow a consistent snake_case pattern with descriptive verb-noun combinations (e.g., collect_snapshot, generate_report, list_findings). However, there are minor deviations like aws_whoami (which uses a command-like name) and cost_explorer_summary_tool (which includes 'tool' redundantly), slightly breaking the pattern.
With 10 tools, this server is well-scoped for AWS audit purposes, covering areas like identity (aws_whoami), cost analysis, reporting, snapshot management, and compliance checks. The count is neither too sparse nor overwhelming, allowing for comprehensive audit workflows without unnecessary complexity.
The tool set appears to cover key audit aspects such as cost analysis, snapshot collection, report generation, and findings listing, but without descriptions, it's unclear if there are gaps in CRUD operations or lifecycle coverage. For example, tools for updating or deleting findings might be missing, potentially limiting agent effectiveness in full audit management.