"Understanding Batch Processing in Computing or Operations" matching MCP connectors:
GET /v1/connectors — MCP directory API referenceMatching Connector Tools:
**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.
Onymu is an MCP server for domain name search, domain availability checking, and social media username lookup. Check a domain name against hundreds of TLDs in one call, including .com, .io, .ai, .co, and country-code extensions. Generate brandable startup names, business names, and product names from a keyword, and instantly see which ones are still available to register. Check username availability across major social networks so a brand name comes with matching handles. Save domains, set favorite TLDs, and recall recent searches to keep name research organized across sessions.
Discovery, OAuth, project operations, and exact project MCP handoff for Spala backend projects.
Read and edit DB Planner database schemas (DBML/SQL), Mermaid diagrams and board layouts from any MCP client. 40 tools with annotations and output schemas. OAuth sign-in, with read and write as separate scopes enforced server-side.
BuyUKeSIM MCP lets AI agents search and purchase global travel eSIMs, UK +44 number eSIMs, and related connectivity services programmatically. Agents can search plans, compare pricing and coverage, create and fund prepaid crypto wallets, purchase eSIMs, and check order status — with no traditional account or KYC workflow.
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/
Read-only IMBA Agent API docs MCP. No register, deposit, buy, or withdraw.
USECREA A persistent project layer for AI agents. USECREA keeps project knowledge, tasks, and progress available across different AI agents, computers, and work environments. Switch agents without copying chats, creating summary files, or starting over.
Human-in-the-loop for AI agents over MCP: durable approvals with a hosted review page & audit trail
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.
Deploy static sites from AI agents: deploy_site publishes files and returns a live URL in seconds.
Generate, edit, and export data-architecture diagrams from your AI. Column lineage, PNG in chat.
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.
AppDeploy turns app ideas described in AI chat into live full-stack web applications
Convert times between IANA zones and detect skipped or ambiguous DST local times.
AI infrastructure design agent. Describe your app in plain English; Riley designs, prices, and deploys AWS or GCP infrastructure with generated Terraform.
Explain a regex in plain English and detect catastrophic backtracking risk.
The PropelAuth Integration MCP Server helps you and your favorite AI agent integrate PropelAuth as quickly and easily as possible into your project. Whether you're integrating PropelAuth into your Next.js project or your FastAPI backend, the Integration MCP Server will ensure your AI agent has the best context possible for a successful integration.
Will this LLM fit on your GPU, multi-GPU rig or Mac? Exact VRAM & KV-cache math. Read-only.
