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Serves your design system and coding standards to coding agents, so they stop guessing.
**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
Never let your agent repeat a bug or linger on a known issue. Search 385+ failure lessons to skip known errors instantly.
Domain security reconnaissance tools for AI agents via Model Context Protocol. 13 security tools — DNS, SSL, HTTP headers, email auth, port scan, propagation, reverse DNS, ASN/BGP, RDAP/WHOIS, subnet calc, and comprehensive security scan — callable from Claude Desktop and any MCP-compatible AI agent. Part of DechoNet. Every tool here is also a free web tool at dechonet.com — no sign-up, no API key — backed by error-fix guides. This package brings the same checks to AI agents.
CometChat docs search + implementation bundles: add chat, voice, video & moderation to your app.
Publish what your agent just made to a public HTTPS link. Pass the content — a page, a report, a deck — and get a live URL that keeps working with no machine online, plus password protection, credential rotation and takedown. 8 tools. The local companion (npm i -g @servelink/serve) adds tunnels to a running dev server.
Publish a complete website to a live URL from your AI assistant — pages, working contact forms, editable content, bookings and an AI chatbot.
Turn documents into structured data with Extend: parse (OCR to markdown), extract fields, classify, split multi-document bundles, and fill PDF forms.
Form backend an agent runs end to end: provision forms, snippets, spam, signed webhooks.
Hubris is an OpenAI-compatible LLM gateway for the Russian market, billed in rubles. This MCP server gives agents access to the model catalog (400+ models with ruble pricing), account balance, and chat completions with full parity to POST /v1/chat/completions. Tools: models_list, models_search (filter by capability/price/context length), models_get_pricing, balance_get, chat_complete. Resources: hubris://catalog/models, hubris://docs/quickstart. Prompt: compare-models. Docs: https://hubris.pw/
Canonicalize Tailwind classes to their short form, and search LunarWerx free dev tools.
Render HTML, URLs, and templates to PDF. AI drafts templates and fixes them from logs.
Agent-first onboarding to Smarter Weather: plans, docs, signup, API keys, MCP config, billing.
Shared error→fix knowledge base for AI coding agents. Search is open with no key; agents query mid-task via REST or MCP and contribute back what they verified worked. New submissions are held from public results until community-upvoted or moderator-approved; disputes stay attached to a fix rather than just lowering its score.
Connect to the MCP Studio SDK MCP server. This server is connected to two sources: the MCP Studio SDK documentation and the GitHub sample application repos. These resources are great for individuals looking to embed MCP Studio SDK into their web applications, and need an easy way to connect to an MCP server that has access reliable resources for AI-assisted engineering workflows.
Push Realm is an MCP server and AI agent knowledge network where agents search proven fixes, publish what worked, and turn dead ends into open problems other agents can close. Compare how agents and tools perform in different topic areas.
Plain-English git via MCP: 22 tools to branch, commit, push, and tag. No git jargon.
Search 77,000+ MCP servers ranked by real adoption data to find the right one for any task.
Official Kudosity Model Context Protocol (MCP) server that allows AI-powered editors (like Cursor and Windsurf) and assistants (like Claude Desktop) to directly explore and execute Kudosity APIs. With MCP, your AI can search API specs, generate code snippets, and run live requests; all without leaving your development environment.
Repos indexed with Moxie Docs can use our MCP to let agents fetch codebase conventions, find affected docs from changes, pull outdated docs to update, and identify orphaned docs to keep up to date. Let your agents keep your documentation accurate and updated at all times.
