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Ultra MCP

ultra-analyze

Perform step-by-step code analysis focusing on architecture, performance, security, quality, or scalability using AI providers like OpenAI or Gemini.

Instructions

Comprehensive code analysis with step-by-step workflow

Input Schema

NameRequiredDescriptionDefault
confidenceNoConfidence level in findings
filesNoFile paths to analyze (optional)
findingsNoAccumulated findings from the analysis
focusNoAnalysis focus areaall
modelNoSpecific model to use
nextStepRequiredNoWhether another step is needed
providerNoAI provider to use
stepNumberNoCurrent step in the analysis workflow
taskYesWhat to analyze in the code
totalStepsNoEstimated total steps needed

Input Schema (JSON Schema)

{ "$schema": "http://json-schema.org/draft-07/schema#", "additionalProperties": false, "properties": { "confidence": { "description": "Confidence level in findings", "enum": [ "exploring", "low", "medium", "high", "very_high", "almost_certain", "certain" ], "type": "string" }, "files": { "description": "File paths to analyze (optional)", "items": { "type": "string" }, "type": "array" }, "findings": { "default": "", "description": "Accumulated findings from the analysis", "type": "string" }, "focus": { "default": "all", "description": "Analysis focus area", "enum": [ "architecture", "performance", "security", "quality", "scalability", "all" ], "type": "string" }, "model": { "description": "Specific model to use", "type": "string" }, "nextStepRequired": { "default": true, "description": "Whether another step is needed", "type": "boolean" }, "provider": { "description": "AI provider to use", "enum": [ "openai", "gemini", "azure", "grok" ], "type": "string" }, "stepNumber": { "default": 1, "description": "Current step in the analysis workflow", "minimum": 1, "type": "number" }, "task": { "description": "What to analyze in the code", "type": "string" }, "totalSteps": { "default": 3, "description": "Estimated total steps needed", "minimum": 1, "type": "number" } }, "required": [ "task" ], "type": "object" }

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