claude mcp add ottersnap-mcp -- npx -y ottersnap-mcp
A pasteable skeleton generated from the repository name. Check the project README for the exact package and arguments.
Star count
0 ★ · zzzjy765/ottersnap-mcp · read from the repository page · (checked 2026-10-16 20:00:20)
Source
collected from the punkpeye/awesome-mcp-servers list · type: MCP server
Harvest history
first seen 2026-10-09 · last seen 2026-10-16 · seen 32× · listed by 7 sources
Score
score 703 · 7 sources · mcp
FAQ (answers come from our records)
How do I install it?
We did not find an install command for this repository (our install coverage is only about 4%). Check its README or releases page.
Who is it for?
We filed it under these tags: MCP 服务. The tags come from the entry itself, not a taxonomy we imposed.
Who maintains it?
repository zzzjy765/ottersnap-mcp;first catalogued 2026-10-09;last seen 2026-10-16。There is no official certification or quality rating here — we record sources and dates only.
MCP (Model Context Protocol) server for **Glint Render** — the web rendering & evidence platform by Moyu. — give Claude, Cursor, Codex and other AI agents **eyes on any web page**: pixel-perfect screenshots, print-ready PDFs and branded OG images from natural language. Quick start Get a free API key at ottersnap.com/dashboard (100 renders/month, no credit card), then add to your MCP client config: Or install globally: Tools | Tool | What it does | |---|---| | render_screenshot | Renders any URL and **returns the image visually** — the agent can actually read the page. Supports full-page, retina 2×, dark mode, element hiding, cookie-banner blocking, iPhone/iPad/Android presets. | | render_pdf | URL or raw HTML → print-ready PDF (A4/Letter/Legal, landscape, margins, header/footer with page numbers). | | create_og_image | Branded 1200×630 social card, returned visually. Seven themes. | | extract_page | URL → structured JSON (title, description, headings, links, images, word count) or clean Markdown — built for RAG and agent pipelines. | | ai_extract | URL + natural-language prompt → structured JSON extracted by LLM. | | code_image | Code snippet → macOS-window syntax-highlighted PNG. | | check_usage | Remaining renders for the configured key. | | workflow_create | Create a **workflow** — an automation that runs steps (screenshot, extract, fetch any public API, AI, email, webhook) on a schedule, when a monitored page changes, or via webhook. | | workflow_list | List your workflows: trigger, steps, enabled state, last run. | | workflow_run | Run a workflow immediately and report every step's result. | | workflow_runs | Recent run history of a workflow. | Example prompts - "Screenshot github.com/trending and tell me which repos mention Rust" - "Create a workflow that watches my landing page and emails me an AI summary whenever it changes" - "Take a dark-mode full-page capture of my landing page and check the footer renders" - "Extract every heading and link from https://example.com/docs as markdown" - "Scrape the product name, price and rating from this URL into JSON"