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MCP vision bridge for text-only coding agents. Analyzes images, performs OCR, compares screenshots, and extracts UI information for agents without native vision support.
Atlas Vision provides 11 vision-focused tools with generally clear naming (verb_noun pattern: analyze_*, ocr_*, compare_*, extract_*) and comprehensive descriptions (avg 150-200 chars). All tools have input schemas with type definitions and parameter descriptions. However, output schemas are not documented, LLMs cannot predict return structure. Error handling is minimal; no recovery guidance or actionable error messages visible. Tool composition is sound (single responsibility), but clipboard tools (analyze_clipboard, ocr_clipboard, etc.) duplicate file-based variants without clear differentiation. The 'should_use_atlas_vision' tool is a meta-decision tool that doesn't fit the vision capability pattern.
Analyze an image from the system clipboard. Requires an image to be copied to clipboard first.
Analyze an image and return detailed visual information in markdown and JSON format. Supports multiple analysis modes (general, diagram, chart, error_screenshot) with configurable detail levels and optional reasoning effort escalation.
Analyze multiple images in a single batch request. Supports up to 10 images with individual prompts and modes.
Analyze a UI screenshot from the system clipboard with framework and style system awareness.
Analyze a UI screenshot with framework and style system awareness. Supports multiple goals: describe, implement, debug, or accessibility review.
Compare two images (before/after) and identify visual differences. Supports focus on layout, text, color, components, or general differences.
Output schemas not documented. LLMs cannot predict return structure (fields, types, pagination). Responses appear to be markdown_json blobs without formal schema definition.
Clipboard tools (analyze_clipboard, ocr_clipboard, analyze_ui_clipboard, diagnose_clipboard) duplicate file-based variants without clear differentiation. LLMs may conflate them or choose wrong variant. Consider consolidating or adding explicit 'when to use' guidance.
No error handling guidance visible. Tools lack recovery hints (e.g., 'If image fails to load, try a URL instead'). No categorization of errors as retryable vs. fatal.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | D | 53 | 2025-06-18+ | v2 |
Diagnose and analyze an image from the system clipboard with detailed diagnostics.
Extract and analyze a specific rectangular region from an image. Useful for focusing on UI elements or specific areas.
Extract text from an image in the system clipboard using OCR.
Extract text from an image using OCR. Supports layout preservation, table extraction, and code block detection.
Determine whether Atlas Vision should be used for a given model and message context. Returns a boolean recommendation.
should_use_atlas_vision is a meta-decision tool (returns boolean recommendation) rather than a capability tool. Unclear why this is exposed as a tool vs. internal logic. Violates single-responsibility principle.
analyze_image_batch accepts up to 10 images but no pagination or streaming guidance. If batch processing is slow, LLMs have no way to know or adapt. Consider documenting latency expectations.