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Validates Bicep deployments to Azure before execution, detecting syntax errors, permission issues, and previewing infrastructure changes. \n \n Supports both Azure CLI ( az ) and Azure Developer CLI ( azd ) workflows, auto-detecting project type via azure.yaml \n Runs Bicep syntax validation, what-if analysis across all deployment scopes (resource group, subscription, management group, tenant), and permission checks with fallback to reduced-permission validation \n Captures detailed what-if resu

Analyze Azure resource groups and generate detailed Mermaid diagrams visualizing resource relationships and architecture. \n \n Discovers all resources within a resource group and maps their interdependencies, including network connections, data flows, identity bindings, and configuration references \n Generates layered Mermaid diagrams with logical grouping by function (Network, Compute, Data, Security, Monitoring) and includes SKU, tier, and configuration details in node labels \n Creates comp

Analyze Azure resource groups and generate detailed Mermaid diagrams showing resource relationships and architecture. \n \n Discovers and analyzes all resources within a specified resource group, capturing configurations, SKUs, network settings, and identity details \n Maps relationships between resources including network connections, data flows, identity bindings, and dependencies \n Generates layered Mermaid diagrams with subgraphs organized by function (Network, Compute, Data, Security, Moni

Query and analyze massive datasets in Azure Data Explorer using KQL for logs, telemetry, and time series data. \n \n Execute KQL queries against billions of records with sub-second performance; discover clusters, databases, and table schemas \n Supports five core query patterns: basic retrieval, aggregation analysis, time series analytics, multi-table joins, and schema exploration \n Includes 4 MCP tools (cluster list, database list, query execution, table schema) with Azure CLI fallback for tim

Secure connectivity between on-premises infrastructure and multiple cloud platforms via VPN and dedicated connections. \n \n Supports four cloud providers (AWS, Azure, GCP, OCI) with provider-specific connection types: Site-to-Site VPN, Direct Connect, ExpressRoute, Cloud Interconnect, and FastConnect \n Covers three hybrid network patterns: hub-and-spoke, multi-region, and multi-cloud architectures with BGP dynamic routing and route propagation \n Includes high-availability configurations with

Real-time Azure service pricing lookup and Copilot Studio agent credit cost estimation. \n \n Queries the Azure Retail Prices API to fetch current pricing for compute, storage, networking, databases, AI, and all other Azure service families across regions and SKUs \n Supports filtering by service name, region, SKU, price type (consumption, reservation, spot), and savings plan options with OData syntax \n Includes cost estimation formulas for monthly and annual workload projections based on usage

Execute Azure deployments for applications with validated infrastructure and deployment plans. \n \n Requires .azure/plan.md with Validated status from azure-validate and prior completion of azure-prepare; will not proceed without both prerequisites \n Executes azd up , azd deploy , terraform apply , and az deployment commands with built-in error recovery and post-deployment verification \n Includes pre-deploy checklist validation, recipe-based deployment workflows, and post-deployment configura

Stateful AI agents on Cloudflare Workers with WebSocket communication, persistent state, and scheduled tasks. \n \n Build agents using the Agents SDK that maintain state across client reconnections and scale via Durable Objects \n Support real-time WebSocket communication, HTTP endpoints, and automatic message history for chat-focused agents \n Schedule background tasks with delay, specific dates, or cron expressions; query state with embedded SQLite \n Extend Agent or AIChatAgent base classes,

Access Azure AI Search, Speech, OpenAI, and Document Intelligence services through unified MCP tools. \n \n AI Search supports full-text, vector, hybrid, and semantic search with built-in AI enrichment for entity extraction and OCR \n Speech service handles real-time and batch speech-to-text transcription, text-to-speech synthesis with neural voices, and speaker diarization \n MCP tools provide direct commands for listing search indexes, querying indexes, transcribing audio, and synthesizing spe

Generate and maintain Terraform code following HashiCorp's official style conventions. \n \n Enforces two-space indentation, lowercase underscore naming, and standard file organization across terraform.tf , providers.tf , main.tf , variables.tf , outputs.tf , and locals.tf \n Requires type and description on all variables and outputs, with validation rules and sensitive flag support for credentials \n Prioritizes for_each over count for dynamic resources, applies security hardening (encryption,