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683,143 tools. Updated 2026-10-21 04:22

"AI Tools for Assisting Architectural Engineers with Engineering Tasks" matching MCP tools:

  • Search open bounties for paid engineering work across software, hardware, MCP servers, CAD, EDA. Filter by category, status, and payout to discover tasks matching your capabilities.
    MIT
  • Get expert AI analysis for complex problem-solving, architectural decisions, and design tradeoffs when confidence is low or planning requires multiple considerations.
    MIT
  • Install a prebuilt governance kit with sealed charters for engineering, federal AI compliance, or EU AI risk councils. Choose from three kits to create a complete institution.
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  • Retrieve Sai Chintamani's 2026 AI engineering learning roadmap. Filter by quarter for specific topics.
    MIT

Matching MCP Servers

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    An MCP server that gives an AI assistant a set of real mechanical-engineering tools. Provides deterministic tools like material properties, beam analysis, unit conversion, and curve fitting for engineering calculations.
    5
    MIT
  • A
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    Converts architectural PDF plans into dimension-verified millimetre geometry, IFC models, and CPU-rendered views, with built-in validation for boundaries, areas, and overlaps.
    MIT

Matching MCP Connectors

  • Decision Layer for AI Agents — 58+ tools, Advisor, MCP. Free key: POST /v1/register {}.

  • 27 engineering compliance and calculation tools for the built environment (UK, EU, UAE).

  • Obtain in-depth architectural details of a binary file, including headers, sections, imports, and exports, to support reverse engineering tasks.
    MIT
  • Log architectural decisions to prevent re-litigation by recording the rationale for future agents.
    MIT
  • Search a knowledge base about AI-native development, agent/harness engineering, and dev practice. Returns ranked matches with concept IDs for full-text retrieval.
    MIT
  • List tasks from D-Tools SI with filters for project, search text, pagination, and deleted or imported status.
    MIT
  • Consult Ollama AI models for architectural decisions, code reviews, and design discussions. Supports sequential chaining for complex multi-step reasoning.
    MIT
  • Retrieve checkable engineering decisions on languages, architectural patterns, and discipline from a curated knowledge base.
    MIT
  • Breaks down complex tasks into interactive, sequential plans with revision and branching for project planning, system design, and architectural decisions.
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  • Scan the codebase to validate imports and technologies against architectural guidelines, identifying forbidden tools to ensure compliance.
    MIT