Skip to main content
Glama

Gemini MCP

by emmron
GitHub
JavaScript
GPL 3.0
14
OverviewInspectNewSchemaRelated ServersReviewsScore
Need Help?View Source CodeReport Issue

mcp__gemini__performance_predictor

Predict system performance under various load scenarios, optimize resource usage, and plan capacity for future growth with AI-driven insights and actionable recommendations.

Instructions

AI-powered performance prediction and optimization recommendations with capacity planning

Input Schema

NameRequiredDescriptionDefault
load_scenariosNoLoad scenarios to predict
metricsNoPerformance metrics to predict
prediction_horizonNoPrediction timeframe12 months
systemYesSystem or code to analyze

Input Schema (JSON Schema)

{ "$schema": "https://json-schema.org/draft/2020-12/schema", "properties": { "load_scenarios": { "default": [ "current", "2x", "10x" ], "description": "Load scenarios to predict", "items": { "type": "string" }, "type": "array" }, "metrics": { "default": [ "response_time", "throughput", "resource_usage" ], "description": "Performance metrics to predict", "items": { "type": "string" }, "type": "array" }, "prediction_horizon": { "default": "12 months", "description": "Prediction timeframe", "type": "string" }, "system": { "description": "System or code to analyze", "type": "string" } }, "required": [ "system" ], "type": "object" }
Install Server

Other Tools from Gemini MCP

Related Tools

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/emmron/gemini-mcp'

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