Skip to main content
Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

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

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
search_evidenceA

$0.00 free search of bounded public StackBench benchmark and failure evidence; use this for evidence-only requests.

check_deployment_fitB

$0.01 USDC on Base mainnet: check model/configuration fit against bounded StackBench capacity evidence.

predict_performanceB

$0.05 USDC: predict configuration throughput, memory, and power from bounded StackBench evidence with confidence, missing metrics, and caveats.

recommend_deploymentC

$0.25 USDC: recommend what to buy or run from bounded StackBench fit, performance, confidence, evidence, caveats, and economics only when supported.

generate_launch_configA

$0.50 USDC: generate deterministic vLLM or llama.cpp launch templates from an exact StackBench recommendation without claiming a launch occurred.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

A3.7/5.0

Scored across 5 tools

Disambiguation4/5

Each tool targets a distinct stage in the evidence-to-deployment workflow. check_deployment_fit and predict_performance are related but clearly separated by fit versus metrics, and recommend_deployment is the only economic recommendation tool.

Naming Consistency5/5

All five tools use consistent lowercase snake_case verb_noun names with concrete action verbs (search, check, predict, recommend, generate), making the naming pattern predictable and readable.

Tool Count5/5

Five tools is appropriate for a specialized advice-and-configuration server. Every tool serves a distinct step in the workflow without redundancy or unnecessary surface area.

Completeness5/5

The server covers the full advisory pipeline: evidence search, fit validation, performance prediction, recommendation, and launch configuration generation. It intentionally stops before executing deployment, which is consistent with its stated purpose.

Maintenance

ActivityMaintained
ResponsivenessNo issues