"Reading data from MySQL database" matching MCP connectors:
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**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
AI product expert answering from live source code, with sources and a verification status.
What CSS you can actually ship today, from live Baseline data and MDN browser-compat-data.
Score the privilege a Chrome MV3 extension takes from its manifest, and diff permission sets.
Dev-registry data: npm/PyPI/Docker/VS Code packages, dep graphs, vulns, 50+ ecosystems.
The official e18e MCP server keeping your agent in check from installing bloated dependencies.
MCP server for YAML: validate & lint, convert between 10 formats, visualize as diagrams, and create/edit your saved diagrams — from your AI editor.
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
Deterministic regex synthesis from labeled examples. Zero LLM, proof matrix, backtracking audit.
Code intelligence for LLMs. Analyze, search, and retrieve code from any public git repository.
Validated Laravel plugin data - health scores, compatibility and vendor trust
Real-time Python package and vulnerability data for AI coding agents.
Generate wiki docs from source code. Supports PowerShell, Python, Go, C#, Java, COBOL.
AI-powered intelligence for your development workflow via Indicate.
Stack intelligence from real production Rails apps. Compare gems, scan a Gemfile. No API key.
MCP server for understanding Javascript internals from ECMAScript specification.
Deep security scans of repos you own from your editor: dependency CVEs, SAST, git-history secrets.
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.
