Skip to main content
Glama
Sign In
katlis

Layout Detector MCP

by katlis
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Related Servers

Alternatives to Layout Detector MCP

No user-submitted related servers found.

    Related Servers

    • PicassoWeb

      blackridder22
      A
      license
      A
      quality
      B
      maintenance
      Analyzes and extracts design tokens, assets, and layout from live websites to enable AI clients to faithfully replicate them, with tools for screenshotting, component inspection, and pixel-diff verification.
      14
      23 npm
      4
      MIT

    • websight

      h34tsink
      A
      license
      Not graded
      quality
      D
      maintenance
      Enables AI agents to see, analyze, and visually verify web page changes through pixel-perfect diffing, theme extraction, layout analysis, and interactive element detection.
      1 npm
      MIT

    • Screenshot MCP Server

      Insightful-Pipe
      A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI assistants such as Claude, ChatGPT, Cursor, and Claude Code to capture full-page, viewport, mobile, and desktop images of web pages, returning signed public URLs. Supports JavaScript rendering, custom viewports, and device emulation for visual documentation, design comparison, and layout analysis.
      MIT

    • Cornea

      AbduljabbarBXR
      A
      license
      Not graded
      quality
      A
      maintenance
      Enables AI agents to inspect web pages deterministically as token-cheap visual geometry instead of pixel dumps, surfacing layout tooling for overlaps, overflow, WCAG contrast ratios, and quality scoring. Agents can pass HTML source or a live URL per call and receive byte-identical, actionable findings they can act on and re-verify.
      1
      MIT

    • screencye

      veloce-ai-idm
      A
      license
      Not graded
      quality
      B
      maintenance
      Eyes for text-only LLMs: decodes screenshots into exact structured text (words, coordinates, sizes, colors) using pure-code CV and OCR. Enables text-only models to reason about UI layouts without vision models or VRAM usage.
      2
      MIT
    Deploy Server
    Shareable, User-Owned Context BackendPeople, applications, and agents read, write, and coordinate together in one context lake. Reach it over MCP, a CLI, a Python SDK, or REST.fulcradynamics.comAd

    TDQS

    A3.7/5.0

    Scored across 3 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose with no ambiguity. analyze_layout focuses on layout analysis and pattern detection, find_assets_in_screenshot handles asset location via template matching, and get_screenshot_info provides basic image metadata. The descriptions clearly differentiate their functions, preventing misselection.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern with snake_case throughout (analyze_layout, find_assets_in_screenshot, get_screenshot_info). The naming is predictable and readable, using descriptive verbs that align with each tool's action.

    Tool Count4/5

    With 3 tools, the count is slightly low but reasonable for the server's purpose of layout detection and screenshot analysis. Each tool earns its place by covering distinct aspects (layout analysis, asset finding, metadata retrieval), though a few more tools might enhance coverage without feeling heavy.

    Completeness4/5

    The tool set covers core operations for layout detection and screenshot analysis, including analysis, asset location, and metadata retrieval. Minor gaps exist, such as no tools for modifying or generating layouts, but agents can work around this with the provided structured data for rebuilding layouts.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources