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"Guidance on Writing Software" matching MCP connectors:

Matching Connector Tools:

  • Scan code for quantum-vulnerable cryptography and get NIST post-quantum migration guidance.

  • Hosted, OAuth-gated endpoint for quantakrypto's post-quantum crypto tools: scan code for quantum-vulnerable cryptography (RSA/ECDH/ECDSA/DH) and get NIST ML-KEM/ML-DSA/SLH-DSA migration guidance over authenticated HTTP — nothing to install. Sign-in required (Google/GitHub/email). Same tools as the open-source @quantakrypto/mcp server; source at github.com/quantakrypto/pqc-tools.

  • Read-only AI coding tools for change verification, release readiness, capacity, and guidance.

  • Stop your AI agents from writing sloppy TypeScript. A toolkit that teaches coding agents like Claude Code, Codex, Cursor, Amp, and more to ship production-ready code in half the time, at half the cost. Docs are available at https://convention.sh/docs

  • The OpenZeppelin Cairo Contracts MCP server generates secure smart contracts in the Cairo language for Starknet environments based on OpenZeppelin templates. It brings OpenZeppelin's proven security and style rules directly into AI-driven development workflows to create safe, production-ready contracts. Key capabilities include providing templates for ERC-20, ERC-721, ERC-1155, Multisig, Governor, and Vesting contracts.

  • ## Skill Catalog The library contains 42 public skills organized by Rails development concern. | Category | Examples | |----------|----------| | Planning | `create-prd`, `generate-tasks`, `plan-tickets` | | Testing | `plan-tests`, `write-tests`, `test-service`, `triage-bug` | | Code quality | `code-review`, `respond-to-review`, `security-check`, `refactor-code` | | Architecture and DDD | `define-domain-language`, `review-domain-boundaries`, `model-domain`, `review-architecture` | | Rails imple

  • Alcheon is an MCP server that gives AI coding agents access to a curated library of 100+ analyzed real-world design systems, letting them recommend reference sites, synthesize design briefs with spacing and color tokens, and generate section-level UI guidance — so AI-built interfaces draw from actual design DNA instead of generic defaults.

  • Source code search for every package on PyPI and npm.