Skip to main content
Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
LOG_LEVELNoControls verbosity of logging. Available levels: debug, info, warn, error, silent (default: info).info

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

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": true
}

Tools

Functions exposed to the LLM to take actions

NameDescription
statusA

Check the current state of the gnaws server: whether resources are loaded, graph size, and available actions. Call this first to understand what tools are available.

scanA

Scan AWS resources live using an AWS profile. This builds an in-memory graph of all resources and their relationships. This is a long-running operation (may take several minutes). After scanning, use 'regions' to list regions, 'detect' to find unused resources, 'export' to export the graph, or 'dump' to save raw data for offline use.

loadA

Load resources from a previously dumped directory (offline mode). No AWS credentials needed. After loading, use 'regions', 'detect', or 'export' to work with the data.

regionsA

List enabled AWS regions from the loaded inventory. Requires 'scan' or 'load' to be called first.

detectA

Detect structurally unused/orphaned resources in the loaded graph. Requires 'scan' or 'load' to be called first. Optionally export findings to a file (.json or .md).

exportA

Export the resource graph to a file. Requires 'scan' or 'load' to be called first. Supported formats: gexf (Gephi), json (sigma.js viewer), md (markdown report).

dumpA

Dump loaded resources to a directory for offline use. Requires 'scan' or 'load' to be called first. The output can later be used with 'load' for offline analysis.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/FabioDominio/gnaws-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server