"Understanding Unrestricted Model Abilities" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Phasio is the operating platform contract manufacturers run on: quoting, production, and back office across additive, CNC, molding, and every process in between. This connector gives LLMs like Claude, ChatGPT and Grok access to your Phasio workspace, so you can interact naturally with your manufacturing data. Commercial - Which customers drive the most revenue? How storefront self-service orders compare against quotes your team builds by hand? Where do carts convert and where they stall? Parts - Inspect any parts volume, bounding box, minimum wall thickness and watertightness, with rendered orthogonal views. Find near-duplicates of a part you've already made before you quote it again. Pricing - Run quotes against parts using your LLM. Ask the model to explain why a part got a certain price, and to tune and refine your pricing equations. Production - Where a job's parts sit on the routing right now? What's been scrapped and why, and which other jobs were caught by the same failed build? Setup - Easily configure pricing equations, shop floor routing and your QMS agentically.
IPStack MCP Adapter turns IPStack's REST APIs into Model Context Protocol tools so any MCP-compatible client can call them directly in conversation. The first release ships IPStack IP geolocation and security lookups (single IP, caller's IP, and bulk). Additional APILayer services are added by registering them in a single config file, so the catalog grows without client-side changes.
The PostNitro MCP server lets AI assistants and agents — Claude (Desktop, Code, and Cowork), Cursor, ChatGPT, and any other Model Context Protocol client — create carousels, image posts, and videos, manage brand kits, audio tracks, and connected social accounts, and schedule posts directly. Instead of writing REST API calls, you connect the server once and your AI assistant gets ready-made tools covering carousel, image, and video generation, brands, audio, social accounts, and scheduling.
Every EmpirioLabs model and platform feature as tools: chat, media, search, jobs, GPU Cloud, agents.
**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
Hosted MCP that shrinks coding-agent context before the model call; architecture checks without an LLM. Zero data retention.
The official Model Context Protocol (MCP) server for RubiConnect — the enterprise platform for RCS (Rich Communication Services) and WhatsApp Business messaging. Connect external AI assistants (such as Claude Desktop, Claude.ai, Cursor, ChatGPT, and autonomous agent pipelines) directly to your RubiConnect messaging workspace to check phone reachability, send rich cards and carousels, trigger bulk campaigns, inspect live inbox conversations, and query messaging analytics.
Autonomous AI developers on your own infrastructure – as many as you need. Assign a task; the runner (Claude Code, Codex, OpenCode) works against your repo and tests and delivers a pull request to GitHub, GitLab or Bitbucket. Any model, your data stays with you.
Connect Claude, Cursor, and other MCP-compatible coding agents to DevTune AI search visibility data with the Streamable HTTP Model Context Protocol server. DevTune exposes a Model Context Protocol (MCP) server so that AI agents can query your AI search visibility data directly. This lets agents like Codex, Claude, Cursor, and other MCP-compatible tools access your metrics and data directly.
Closed-source remote MCP: model benchmarks, costs, HN signals, tech registry.
The official Model Context Protocol server for Ambee. It gives any MCP-compatible AI assistant — Claude, ChatGPT, Cursor, VS Code, Ollama, and more direct access to live air quality, pollen, and weather data. To get started, including information on signing up and obtaining your Ambee key, check out the Ambee documentation on https://docs.ambeedata.com
