Image Reader
БесплатноНе проверенEnables AI agents to read images with metadata, OCR text, regions, and citeable evidence without relying on generative LLMs.
Описание
Enables AI agents to read images with metadata, OCR text, regions, and citeable evidence without relying on generative LLMs.
README
🖼️ Image Reader MCP
Your agent looked at the image. Did it see the truth?
Evidence-first image reading for AI agents. One call turns any local image into an Agent Media Twin — dimensions, metadata, optional OCR with bounding boxes, and trust warnings you can cite without asking a vision LLM to guess.
npm version License CI/CD TypeScript
Local-first · One smart read_image call · Evidence with bbox + provenance · 23 tests
SOTA family roadmap: docs/roadmap/sota-family-roadmap.md.
⭐ Star this repo if agents should read images with facts, not vision-model guesses. · Quick start · See it work · Why not vision LLM guess?
Part of the Sylphx Reader portfolio — orchestration and portfolio ADR live in smart-reader-mcp.
The problem
Images are not filenames. They are pixels, EXIF, orientation, embedded GPS, hidden metadata, and text that only exists if you OCR it with geometry.
Most agent stacks route images through a vision LLM and get a plausible description. Dimensions get rounded. OCR text gets paraphrased. Metadata disappears. Citations become "the model said so." Then the agent hallucinates — confidently.
Image Reader MCP is built for the moment your agent needs measurable facts about an image, not a creative caption.
Why not vision LLM guess?
| Typical vision path | Image Reader MCP |
|---|---|
| "Describe this image" | Return filename, mime, dimensions, and structured metadata |
| Paraphrased OCR | Optional Tesseract lines with bounding boxes and confidence |
| GPS and EXIF leak into context | GPS redacted; trust warnings for suspicious metadata |
| No provenance | Agent Media Twin JSON with measurable, citeable fields |
| Cloud API by default | Local-first — sharp + exifr on your machine |
| Ship and pray | 23 unit tests on schema, metadata, OCR hooks, safety limits, doctor, and release gate |
See it work
Install once. Call once.
claude mcp add image-reader -- npx @sylphx/image-reader-mcp
{
"path": "/absolute/path/to/photo.jpg",
"include_metadata": true,
"include_ocr": true
}
read_image inspects the file locally and returns an Agent Media Twin — no
generative LLM required:
{
"filename": "photo.jpg",
"mime": "image/jpeg",
"dimensions": { "width": 4032, "height": 3024 },
"orientation": 1,
"metadata": {
"Make": "ExampleCamera",
"Model": "Pro X",
"DateTimeOriginal": "2026-03-15T14:22:10"
},
"ocr": {
"available": true,
"lines": [
{
"text": "INVOICE #1042",
"bbox": { "x": 120, "y": 48, "width": 310, "height": 36 },
"confidence": 92
}
]
},
"trust_warnings": []
}
Abbreviated shape — optional OCR skips gracefully when Tesseract is not installed.
MCP Tool Surface
| Tool | Use it when the agent needs to... |
|---|---|
read_image |
Read a local image and return dimensions, mime, metadata, optional OCR, and trust warnings. |
Supported formats: PNG, JPEG, GIF, WebP, TIFF, and other formats sharp can decode.
Quick Start
Claude Code
claude mcp add image-reader -- npx @sylphx/image-reader-mcp
Claude Desktop
Add this to claude_desktop_config.json:
{
"mcpServers": {
"image-reader": {
"command": "npx",
"args": ["@sylphx/image-reader-mcp"]
}
}
}
Any MCP Client
npx @sylphx/image-reader-mcp
Node.js >=22.13 is required. Optional OCR uses a local Tesseract adapter when
installed — no cloud credentials required by default.
Security model
- Local-first —
read_imageresolves paths on the local machine; no cloud vision API by default. - GPS redaction — location metadata is stripped from agent-facing output unless explicitly opted in.
- Size and format limits — oversized or unsupported inputs return structured errors, not partial guesses.
- Optional OCR — Tesseract runs locally when installed; missing OCR is reported as
available: false, not silent failure. - Trust warnings — suspicious EXIF, orientation, or metadata anomalies surface in
trust_warningsfor agent verification.
Release proof
Claims are backed by CI benchmark:release-gate and the shipped-path matrix (Rust-default route, no legacy Node engine on primary tools).
bun run benchmark:release-gate
Artifact: benchmark-artifacts/image_reader_release_gate.json — must report status: passed before release.
Development
git clone https://github.com/SylphxAI/image-reader-mcp.git
cd image-reader-mcp
bun install
bun run build
bun test
bun run doctor
bun run benchmark:release-gate
Useful checks:
bun run check
bun run typecheck
bun run validate
bun run benchmark:release-gate
Example read_image requests live in examples/.
Support
- Issues
- npm package
- Portfolio orchestration: smart-reader-mcp
Help this reach more builders
If vision-model guesses have wasted your context, your citations, or your trust in agent output, you are exactly who this project is for.
⭐ Star the repo — it is the fastest way to help more agent builders find evidence-first image reading. Share it in your MCP client setup, team wiki, or agent stack README.
Discovery (in progress)
| Channel | Status |
|---|---|
| Glama MCP directory | Listed — claim server for full discoverability |
| Official MCP Registry | Listed — io.github.SylphxAI/image-reader-mcp @ v0.1.0 |
| TensorBlock MCP Index PR #1113 | Open — multimedia/document processing listing |
| MCP servers community issue #4500 | Open — community server highlight |
| mcp.so listing issue #3068 | Open — directory submission request |
| mcpservers.org submit | Not listed yet — free web-form submission |
Know another MCP directory? Open an issue with the link.
License
MIT © SylphxAI
Установка Image Reader
У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.
▸ github.com/SylphxAI/image-reader-mcpFAQ
Image Reader MCP бесплатный?
Да, Image Reader MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для Image Reader?
Нет, Image Reader работает без API-ключей и переменных окружения.
Image Reader — hosted или self-hosted?
Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.
Как установить Image Reader в Claude Desktop, Claude Code или Cursor?
Открой Image Reader на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
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