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521,628 tools. Updated 2026-09-06 11:42

"Enhancing AI for Coding" matching MCP tools:

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  • Ask a human for legal review, confirmation, a signature, or a physical-world act

  • Free check/board/name; paid bid/report 0.05, 1c fx/wx/lookups, news 0.001.

  • Search across per-video summaries of curated AI/coding YouTube channels using free-text queries or filters for topics, channels, and language.
    MIT
  • Begin a new AI coding session by specifying a development task, enabling persistent memory and project tracking for the assistant's work.
    MIT
  • Identify common LSL pitfalls to prevent AI coding errors. Filter pitfalls by category or AI source for targeted guidance.
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  • Search AiWiki for AI-coding pitfalls and LLM privacy protection answers. Get cited explanations and solutions for recurring AI failures.
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  • List downloadable doctrine and agent asset artifacts to import as native skill or rule files into your AI coding tool. Returns assets with format, version, download URL, and platform target.
    MIT
  • Convert an annotation into a ready-to-paste coding prompt formatted for your target AI assistant (Claude, Copilot, Cursor, etc.) using a deterministic template with no AI spend.
    MIT
  • Save permanent operational rules learned during coding sessions. These rules persist and auto-surface in search results to prevent AI agents from repeating mistakes.
    Business Source 1.1
  • Verifies all project repositories have no uncommitted changes and documentation is up-to-date, returning a checklist of required actions to resolve before ending a coding session.
    Business Source 1.1
  • Get a second opinion from another AI model or route a task to a specialized model. Choose coding, reasoning, budget, or free modes, or specify a custom model for the job.
    MIT
  • Retrieve LLM-readable documentation for a module, including rules and implementation notes, to guide coding against the module contract.
    MIT
  • Retrieve the coding conventions that apply to your current project context to ensure compliance and consistency before making changes.
    MIT
  • Delegate a scoped coding task to an external AI worker in an isolated git worktree with independent verification.
    MIT