@gnaws/mcp
Allows AI agents to scan AWS accounts, build resource relationship graphs, and detect unused/orphaned resources across 65+ AWS services.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@@gnaws/mcpscan my AWS account and find any unused resources"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
@gnaws/mcp
Let your AI agent see what's beneath your cloud.
MCP (Model Context Protocol) server for @gnaws/core — expose AWS resource scanning, graph building, and unused resource detection as tools for AI agents.
What is this?
An MCP server that gives AI agents (Claude, Kiro, Cursor, etc.) the ability to:
Scan your AWS account and build a resource relationship graph
Load previously dumped data for offline analysis
Detect unused/orphaned resources (detached volumes, unassociated IPs, empty load balancers, etc.)
Export the graph to GEXF (Gephi), JSON (sigma.js), or Markdown
Dump raw resource data for later use
Related MCP server: AWS SRA Verify MCP Server
Installation
npm install -g @gnaws/mcp
# or run without installing:
npx @gnaws/mcpRequires Node.js >= 24.
MCP Client Configuration
Kiro
Add to .kiro/settings/mcp.json:
{
"mcpServers": {
"gnaws": {
"command": "npx",
"args": ["@gnaws/mcp"]
}
}
}Claude Desktop
Add to claude_desktop_config.json:
{
"mcpServers": {
"gnaws": {
"command": "npx",
"args": ["@gnaws/mcp"]
}
}
}VS Code (GitHub Copilot)
Add to .vscode/mcp.json:
{
"servers": {
"gnaws": {
"command": "npx",
"args": ["@gnaws/mcp"]
}
}
}Cursor
Add to .cursor/mcp.json (project) or ~/.cursor/mcp.json (global):
{
"mcpServers": {
"gnaws": {
"command": "npx",
"args": ["@gnaws/mcp"]
}
}
}Available Tools
Tool | Description | Requires |
| Check server state (loaded? how many nodes/edges?) | — |
| Scan AWS resources live with a profile | AWS credentials |
| Load from a dump directory (offline) | Dump path |
| Find unused/orphaned resources |
|
| Export graph to gexf/json/md |
|
| Save raw data for offline use |
|
| List enabled AWS regions |
|
Example Conversations
User: Show me the unused resources in my AWS account
Agent: callsscanwith profile → callsdetect→ presents findings
User: Load the dump from ./data and export a graph
Agent: callsloadwith path → callsexportwith format "gexf"
User: What's the state of the gnaws server?
Agent: callsstatus→ reports no data loaded, suggestsscanorload
Features
Progress notifications — long-running scans report progress to the agent
Error handling — every tool returns structured errors with actionable guidance
Workflow guidance — tool responses tell the agent what to call next
Offline mode — load from dumps without AWS credentials
65+ AWS services — EC2, Lambda, S3, RDS, ECS, EKS, DynamoDB, and many more
Log Level
All logging goes to stderr (safe for MCP stdio transport). Control verbosity with:
LOG_LEVEL=debug npx @gnaws/mcpAvailable levels: debug, info, warn, error, silent (default: info).
Development
# Build
npm run build
# Dev mode (tsx with hot reload)
npm run dev
# Type-check
npm run typecheck
# Lint
npm run lint
# Test with MCP Inspector
npx @modelcontextprotocol/inspector npx @gnaws/mcpContributing
See CONTRIBUTING.md.
Support
If GNAWS saves you money on your AWS bill, consider sponsoring the project.
License
AGPL-3.0 — see LICENSE.
Not affiliated with or endorsed by Amazon Web Services.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
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