MCP server

Moltline Vision Maths

com.moltlinestudio/vision

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

Image header probing, bbox conversion, resize plans and colour maths. 4 of 6 free.

Website Source

At a glance

Type

MCP server

Publisher

moltlinestudio.com (verified by the MCP Registry)

Status

Working at last check

Tools

6

Token cost

About 3,126 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http vision https://mcp.moltlinestudio.com/vision

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.vision]
url = "https://mcp.moltlinestudio.com/vision"

Gemini CLI

{"mcpServers":{"vision":{"httpUrl":"https://mcp.moltlinestudio.com/vision"}}}

Cursor

{"mcpServers":{"vision":{"url":"https://mcp.moltlinestudio.com/vision"}}}

VS Code

{"servers":{"vision":{"type":"http","url":"https://mcp.moltlinestudio.com/vision"}}}

Antigravity

agy mcp add vision https://mcp.moltlinestudio.com/vision

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"vision","server_url":"https://mcp.moltlinestudio.com/vision","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"vision","server_url":"https://mcp.moltlinestudio.com/vision"}

Tools

• bbox_convert ~610 tokens
  Convert bounding boxes between COCO, Pascal VOC and YOLO. FREE. The three formats disagree on everything: COCO is [x, y, width, height], VOC is [x1, y1, x2, y2], YOLO is [cx, cy, w, h] normalised to the image. Getting this wrong produces boxes that look plausible and quietly ruin every metric. Typi
• colour_check ~394 tokens
  Check a colour pair against the WCAG contrast thresholds. FREE. Uses the WCAG 2 relative-luminance formula, so the number matches what an accessibility audit will report. Typical input {"foreground": "#767676", "background": "#ffffff"} returns {"contrast_ratio": 4.54, "AA": true, "AAA": false, "req
• detection_metrics ~632 tokens
  Score detections against ground truth and show the working. PREMIUM (license). Greedy matching at the IoU threshold, highest-confidence prediction first, each ground-truth box matched at most once - the standard protocol. Reports per-class precision, recall and F1, and average precision by the all-
• image_probe ~389 tokens
  Read an image's format and pixel size from its header alone. FREE. Dimensions live in the first few dozen bytes of PNG, JPEG, GIF, BMP and WebP, so a base64 prefix is enough - you do not need to send the whole file, and nothing is decoded. Typical input {"data_base64": "iVBORw0KG..."} returns {"for
• nms ~549 tokens
  Remove duplicate detections of the same object. PREMIUM (license). Greedy non-maximum suppression: keep the highest-scoring box, drop everything overlapping it above the threshold, repeat. Ties break on the earlier index, so the result is deterministic rather than dependent on sort stability. Typic
• resize_plan ~552 tokens
  Work out the exact scale, padding and crop for a model input size. FREE. Returns the numbers you need to transform boxes alongside the image, which is the step that usually gets skipped. Typical input {"width": 1920, "height": 1080, "target": "yolo_640"} returns {"scale": 0.3333, "resized": [640, 3

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