Log inSubmit server
Iris logo

Iris

Reads local images with metadata, optional Tesseract OCR, citeable crops, hashes, and same-size pixel comparisons.

InstallRepositoryWebsite
Full README Compare alternatives Embed widget Claim this listing

Install Iris

Pick your client, then add it in one click or paste the config.

STDIONode.js
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "iris-2": {
      "command": "npx",
      "args": [
        "-y",
        "@sylphx/anymd"
      ]
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

We couldn’t confirm it starts correctly

We ran the install command but it didn't respond within our test window — this can mean a slow first-time install rather than a real problem.

npx -y @sylphx/anymd

No response to initialize.

This is an experimental automated check and can have false negatives — missing environment variables, a slow cold install, etc. It doesn’t necessarily mean something’s wrong. Last checked 19d ago.

Overview

The Iris MCP server inspects local images and returns measured geometry, format, metadata, hashes, crops, and pixel-difference data. Its read_image tool leaves OCR disabled by default, while an explicit option or quality profile invokes local Tesseract and returns text with bounding boxes. Use it when an agent needs evidence from screenshots or other image files rather than generative vision guesses. The repository is archived after merging into anymd, but the documented npm command remains available.

Use cases

  • Inspect screenshot dimensions and metadata before processing
  • Extract local image text with bounding boxes when needed
  • Create hashed, citeable crops from screenshots
  • Compare same-size captures for changed pixels
  • Verify whether OCR was available instead of inferring text

Key features

  • Local image metadata and geometry inspection
  • Opt-in Tesseract OCR with bounding boxes
  • Region crops with hashes and optional PNG bytes
  • Same-dimension pixel comparison
  • Source hashes and trust warnings

Tools4

What Iris lets your agent do. Expand a tool for its parameters.

Self-reported~93 tokens of context

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

Not checked yetLast checked 1d ago

We have not completed a health check for this listing yet.

0/9 checks healthy over the last 37d

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 14d ago via OSV.dev · @sylphx/anymd (npm)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars2Stargazers on the source repository.
npm downloads23kPackage downloads in the last 30 days.
Last commit1mo agoMost recent push to the default branch.
Install checkInconclusiveDidn't respond in our test window — often a slow first install.
Tools exposed4Callable tools this server registers over MCP.
Directory activity3 viewsConfig copies, upvotes, and views on AllMCPs.

How Iris works

What the Iris MCP server does

The Iris MCP server gives an MCP client structured facts about local image files. It can report dimensions, format, pixel count, metadata, source hashes, and trust warnings without using a generative vision model. OCR is an opt-in operation, so a normal image read does not silently turn visual content into a transcription.

The server is suited to workflows where an agent must cite or verify image evidence. For example, it can identify the geometry of a screenshot, extract requested text with its location, isolate a region for reference, or measure changes between two captures. It does not provide general image understanding beyond the documented measurements and operations.

How it works

Iris runs as a stdio MCP server from the npm package @sylphx/iris. A client sends local file paths and tool arguments, and the process returns structured results. No API key is required. OCR runs locally through the tesseract executable when requested; the default OCR language is eng.

read_image combines image geometry and metadata inspection, with an optional region and optional OCR. image_probe is narrower: it returns format, dimensions, pixel count, and a source hash, without cropping or OCR. crop_region produces the bounds and hash for one region and can include PNG bytes when requested. compare_images reports changed pixels and a changed bounding box for two images with matching dimensions.

Setup and configuration

Run the server with:

Terminal
npx -y @sylphx/iris

For Claude Code, the documented command is:

Terminal
claude mcp add iris -- npx -y @sylphx/iris

Other documented client configurations use npx as the command and -y, @sylphx/iris as its arguments. The repository lists Claude Desktop, Cursor, VS Code, and Codex with this configuration style. OCR requires the tesseract binary to be available on PATH; the server itself does not require an API key.

Tools and capabilities

  • read_image: Reads one local image, returning geometry and metadata. OCR can be enabled with include_ocr: true or profile: "quality"; an explicit include_ocr: false takes precedence.
  • image_probe: Returns format, dimensions, pixel count, and source hash without OCR or cropping.
  • crop_region: Returns a citeable region’s bounds and hash, with optional PNG region data.
  • compare_images: Finds changed pixels between equal-sized images without resizing either input.

OCR results contain text, bounding boxes, and confidence values. The response can identify an unavailable OCR dependency through the OCR_UNAVAILABLE gap rather than fabricating text.

Limitations and notes

The default file-size limit is 32 MiB. A cropped region cannot exceed 67,108,864 pixels. Files that are too large or cannot be decoded fail instead of being returned as successful reads. GPS metadata is always redacted, and the material does not describe an option to restore it.

compare_images requires identical dimensions and performs no resizing. OCR is not automatic, and missing Tesseract means OCR is unavailable even though non-OCR image inspection can remain successful. The Iris MCP server repository was archived on September 25, 2026 after its functionality was merged into anymd, which also reads other document and media formats. This listing therefore describes a documented package and interface from an archived repository, not an actively developed codebase.

Read the full README View source on GitHub

Reviews

No reviews yet — be the first to share how it worked for you.

Frequently Asked Questions about Iris

Iris is an MCP server that connects to local image files and exposes read_image, image_probe, crop_region, and compare_images. It reports image geometry, metadata, hashes, crops, pixel changes, and optional local Tesseract OCR with bounding boxes. OCR is requested rather than assumed, so agents can distinguish measured image facts from unavailable data.

Run `npx -y @sylphx/iris` to start Iris as a stdio MCP server. Claude Code can use `claude mcp add iris -- npx -y @sylphx/iris`; Claude Desktop, Cursor, VS Code, and Codex use an MCP configuration with `npx` and the package arguments.

Yes, Iris works with Cursor through an MCP configuration using `npx -y @sylphx/iris`. No API key is required. OCR additionally needs the local `tesseract` binary on `PATH`.

Iris extracts text with local Tesseract only when OCR is requested. Set `include_ocr` to true or use the `quality` profile with `read_image`; OCR results include text, bounding boxes, and confidence. The default behavior performs no OCR.

Related MCP servers

All in Multimedia Process All alternatives
Add a badge to your READMEShow it’s listed — live SVG, Markdown or HTML.

AllMCPs Directory Badge

Full Badge Customizer

Showcase your server listing on GitHub or your project documentation. Embed this dynamic SVG badge to highlight official listing status and live engagement.

Badge Style:
Live Dynamic SVG PreviewIris AllMCPs Directory Badge
Markdown (GitHub README)
[![AllMCPs](https://allmcps.com/api/badge/iris-2?style=directory)](https://allmcps.com/mcp/iris-2)
HTML Embed
<a href="https://allmcps.com/mcp/iris-2"><img src="https://allmcps.com/api/badge/iris-2?style=directory" alt="Iris on AllMCPs" /></a>