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163,151 tools. Last updated 2026-05-30 15:34

"Resources for Frontend Coding" matching MCP tools:

  • Create a full-stack decentralized application on Aptos blockchain with resources for Move smart contracts, project management, and frontend development.
    Apache 2.0
  • Build a UI frontend for Aptos dApps by generating resources from frontend directories. Use this tool for guidance on developing dApp interfaces on the Aptos blockchain.
    Apache 2.0
  • Detects critical secure coding issues in C/C++ source code, including stack buffer overflows, unsafe function usage, format string exploits, and memory leaks.
    MIT

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  • Give your AI agent a phone. Place outbound calls to US businesses to ask, book, or confirm.

  • The world's cultural intelligence infrastructure layer. Kultur.dev gives every AI agent, coding assistant, and enterprise platform the ability to understand 195 countries' cultural norms, geopolitical sensitivities, and business etiquette. 11 MCP tools including cultural context analysis, Hofstede 6-D scoring, geopolitical heatmaps, content localization, holiday calendars, and adaptive risk scoring powered by a 645K+ document knowledge base. Essential for any AI building products, content, or co

  • Create TypeScript clients for frontend applications to interact with backend API endpoints, simplifying API integration and type-safe communication.
    MIT
  • Routes coding tasks to the optimal AI model by analyzing task complexity, balancing cost and capability for code generation, refactoring, and algorithm design.
    MIT
  • Identifies resources missing tags or labels across Azure or GCP. Untagged resources hinder cost attribution and team accountability, so this tool pinpoints them for remediation.
    MIT
  • Refines vague coding requests into structured, agent-specific prompts by extracting requirements, filling edge cases, and running quality checks. Ideal for under-specified tasks before handing to a coding agent.
    MIT
  • List available models, tests, sources, and other resources within a dbt project to understand project structure, identify dependencies, and select resources for operations.
    MIT
  • Compose final frontend-ready Blueprint JSON from a grouping artifact. This produces a structured project map for AI agents.
    MIT
  • Retrieve current status details for the Smart Coding MCP server, including version, workspace configuration, indexing progress, and cache information to monitor the semantic search system's operational state.
    MIT