"Understanding Cursor Rules in Programming or User Interfaces" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
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.
Check that your AI is being logical. Free tool that mathematically catches contradictions in agent reasoning. No account needed. Also offers paid guardrails that converts natural language to formal verification proofs, that anyone can check succinctly.
**Can AI actually read your page?** ChatGPT, Perplexity, Claude and Google's AI Overviews fetch pages very differently from your browser — no JavaScript, tight timeouts, and a robots.txt rulebook of their own. Lekta fetches a URL exactly the way they do and grades what survives, **A+ to F**. This is the technical half of **AEO** (answer engine optimization) and **GEO** (generative engine optimization): before a model can cite you, it has to be able to fetch you, parse you, and find one sentence worth quoting. **The loop this server was built for:** `Audit https://mysite.com/pricing with Lekta, apply the fixes it lists, audit it again, and show me the difference.` Your agent gets a graded verdict, a ranked fix plan with the exact markup to paste, and a diff that proves the change landed. Repeat until A+. **Four layers, 100 points:** **Access** 25 — do the ~17 AI crawler tokens get past robots.txt? **Indexability** 25 — how much content survives without JavaScript? **Answerability** 30 — is there a single quotable sentence an engine can lift? **Recency** 20 — can a model tell when this page was last true? **What this is not:** a rank tracker. Lekta will not tell you how often ChatGPT mentions your brand. It tells you whether your page can be read and quoted when it does — the part you can actually fix. **No black box.** Every finding cites its basis — an RFC, a vendor doc, or a dated measurement we ran. The engine is versioned with a public changelog: a score never moves without a published shift table. **Tools:** `lekta_audit` (fresh fetch) · `lekta_report` (cached read) · `lekta_fix_plan` (ranked, paste-ready) · `lekta_diff` (before/after) · `lekta_my_sites` Listing tools is open. Tool calls need a free key from lekta.dev/en/panel/api — send `Authorization: Bearer lekta_…` or `x-api-key`. Cached reads, fix plans and diffs cost nothing; only fresh fetches count against the daily limit. **Topics:** AEO · GEO · AI SEO · LLM SEO · answer engine optimization · generative engine optimization · AI crawler access (GPTBot, ClaudeBot, PerplexityBot, Google-Extended) · JavaScript-free indexability · structured data · content freshness
Stateless TypeScript and JavaScript code intelligence for AI agents. Find semantic symbol references, resolve imports and importers, inspect callers and callees, and analyze change impact with compiler-backed evidence. No repository indexing or OAuth required.
Runs your code against a contract; HELD or BROKE at the exact input. Deterministic. 0.10 USDC/call.
Detect malicious or vulnerable npm packages: registry search, OSV.dev and GitHub advisory lookups
Rams is a design reviewer for UI code. The MCP server puts the hosted engine inside a coding agent: the agent passes files to the review_files tool and gets back a 0–100 score with file:line issues and concrete fixes — accessibility, color, typography, spacing, components, UX, motion, craft, and native SwiftUI. Same engine and scoring as the Rams GitHub App. 258 rules, published at rams.ai/rules. Free tier: 30 reviews/month.
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
Repository knowledge graph MCP server for codebase understanding and debugging.
Explain a regex in plain English and detect catastrophic backtracking risk.
Stateless TS/JS compiler facts for agents: references, imports, impact. No repo index or OAuth.
Rust crate vulns: CVEs, patched versions. $0.01/query. Register in-session — free testnet funds.
Scan any public GitHub MCP-server repo for security issues. 37 MCP-specific L1 rules, 8 languages.
Honest library picks for coding agents in 25-360 tokens. Tells your agent what NOT to install.
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ESLint rules key count, body discarded
Repository evidence for agents before they adopt dependencies, enter codebases, compare, or merge.
Zero-install security baseline for AI coding agents — OWASP/CWE-cited rules over MCP.
Detect malicious or vulnerable npm packages: registry search, OSV.dev and GitHub advisory lookups
Design review for UI code: 291 rules, scored 0-100 with fixes and git-applyable patches.
