snapWONDERS MCP (local)

com.snapwonders由 snapwonders.com 發布v0.1.3更新於 Oct 29, 2026

Local snapWONDERS MCP: hide, reveal, analyse and convert files on your own machine

發布方自己的服務:snapWONDERS Vaultify

概覽

AI 產生的概覽

本機 MCP 伺服器,讓助手透過 snapWONDERS 在使用者電腦上對圖片與影片做鑑識分析、格式轉換、藏入檔案與取出隱藏內容。

可以做什麼
  • 對本機圖片或影片做鑑識分析:A–F 評級、中繼資料暴露(GPS、裝置指紋、編碼器特徵)、竄改痕跡、隱藏內容,可選人臉偵測與 OCR
  • 把檔案藏進封面圖片或影片,並將結果存到磁碟
  • 用通關語從圖片或影片取出隱藏內容並寫入磁碟
  • 在 jpeg、png、webp、avif、heic、jxl 等圖片格式與 mp4h264、mp4h265、webm、mkv、mov 等影片格式之間轉換
適用情境
適合要處理的檔案就在自己的電腦上、而用戶端沒有終端機可供助手操作的情況,此時遠端伺服器無法取得這些檔案。每個工具一次完成整項任務,並把輸出寫回本機磁碟。
執行需求
以 Python 套件透過 stdio 在本機執行(uvx 或 pip install snapwonders-mcp),僅支援桌面用戶端。需要 snapWONDERS API 金鑰,放在 SNAPWONDERS_API_KEY 環境變數中,來自已通過電子郵件驗證的免費帳號。處理時檔案會上傳到 snapwonders.com,因此需要 HTTPS 網路連線。
安裝前請注意
指定的檔案會上傳到 snapWONDERS 處理,任何可讀路徑都可能被送出,包括敏感檔案;核准工具呼叫前請先確認路徑。API 金鑰只放在環境變數中,但 hide_file 與 reveal_file 的通關語是以工具參數傳入,可能出現在模型上下文、用戶端日誌與對話紀錄中。藏入用的通關語不會被保存也無法重設,遺失後藏入的檔案無法取回。工具會寫入檔案到磁碟。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 snapWONDERS MCP (local),將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

[snapWONDERS MCP Server]

snapWONDERS — Expose what's hidden. Hide what's yours.

[snapWONDERS MCP server on Glama] [snapWONDERS Vaultify MCP connector – tool definition quality and endpoint health on Glama]

snapWONDERS MCP

A local MCP server that lets an AI assistant work on files on your own machine — hide a file inside a photo, reveal hidden content, run forensic analysis, or convert between formats.

Claude Desktop ──stdio──▶ snapwonders-mcp ──HTTPS──▶ snapwonders.com/api   (your machine)          (your machine)

Why this exists

snapWONDERS already has a remote MCP server at https://snapwonders.com/mcp, and for orchestration it works well. But it runs on our servers — so it cannot see your files, and MCP tool calls carry JSON rather than bytes. An assistant with a photo on your desktop could create a session and then have nowhere to put the file.

This server runs where your files are. You give it a path, it reads the file locally and uploads it over HTTPS alongside the conversation. That is the whole difference, and it is what makes snapWONDERS usable from Claude Desktop, which has no terminal for an assistant to fall back on.

Results come back the same way: a hide, reveal or convert writes the output to your disk and tells the assistant where it landed — not an asset id you would need a separate HTTP client to redeem.

Install

You need an API key from https://snapwonders.com/profile/api-keys (free account, and the address must be verified — an unverified account's keys are always rejected).

Nothing to install ahead of time if your client can run uvx:

bash
uvx snapwonders-mcp

Or install it properly:

bash
pip install snapwonders-mcp

Configure your client

Claude Desktop

%APPDATA%\Claude\claude_desktop_config.json on Windows, ~/Library/Application Support/Claude/claude_desktop_config.json on macOS:

json
{  "mcpServers": {    "snapwonders": {      "command": "uvx",      "args": ["snapwonders-mcp"],      "env": { "SNAPWONDERS_API_KEY": "sw_your_key_here" }    }  }}

Claude Code

bash
claude mcp add snapwonders --env SNAPWONDERS_API_KEY=sw_your_key_here -- uvx snapwonders-mcp

Cursor

~/.cursor/mcp.json (global) or .cursor/mcp.json (project):

json
{  "mcpServers": {    "snapwonders": {      "command": "uvx",      "args": ["snapwonders-mcp"],      "env": { "SNAPWONDERS_API_KEY": "sw_your_key_here" }    }  }}

The key is read from the environment, never taken as a tool argument — so it does not pass through the model's context, where it would end up in transcripts and logs.

Passwords are different, and you should know it. hide_file and reveal_file take the passphrase as a tool argument, because only the user can supply it and it changes per call. That means it does pass through the model's context and may appear in client logs and transcripts. There is no way around that in an assistant-driven flow — but the care taken with the API key does not extend to the passphrase, so treat anything you hide through an assistant accordingly.

This server can upload any file you can read. That is the point of it — an assistant asks for a path and the file is sent to snapWONDERS for processing. It also means a request like "analyse ~/.ssh/id_rsa" would do exactly that, and an assistant following instructions from a web page or document it has read could try to use it that way. Your MCP client's tool-approval prompt is the real gate: read the path in the tool call before approving it.

Tools

ToolWhat it does
analyse_fileForensic analysis of a local image or video — A–F grade, metadata exposure, manipulation evidence, hidden content. Optional face detection and OCR.
hide_fileConceal a file inside a cover image or video, and save the result to disk.
reveal_fileExtract content hidden in an image or video, and save it to disk.
convert_fileConvert an image or video to another format, and save the output to disk.

Four tools, each a whole task. The REST API underneath is a session → upload → job → poll → results sequence; exposed one call per step, a model has to carry five-step state and will sometimes get it wrong. The orchestration lives here in Python instead, where it is deterministic.

Passwords for hide_file are not recoverable. They are never stored, and there is no reset. Be sure the user knows the passphrase before hiding something with it.

When you would use the remote server instead

https://snapwonders.com/mcp needs no install and is right when the files are already somewhere the server can reach, or when you only want session and job orchestration. Use this local server when the files are on the user's machine — which, for a desktop assistant, is almost always.

Which upload it uses

Whichever fits, and you never choose: the Python SDK sends anything under the server-reported cap (currently 95 MB) as a single direct upload, and falls back to the resumable TUS protocol above it.

Why snapWONDERS exists

This project started with my son, Huey.

Huey lost his eyesight and was legally blind from the age of four. Years ago, in the car, while we were working on Hueyify together, he insisted the idea could be applied to digital media: stories embedded inside a photo, so that people with vision impairments could get the personal context, the memory and the feeling behind it. Hidden from everyone else. Only for the person it was meant for.

He was excited at the thought of it. I'll admit the technical difficulty put me off, and I was vocal about it. The look of disappointment kept returning to me, because to Huey it all made sense. We lost Huey at sixteen. I could never let go of that conversation.

snapWONDERS came first, to understand what digital media actually contains and who can see it. Vaultify came after, and it is the closest thing I've built to what Huey described. As of September 2026, snapWONDERS and Vaultify have processed more than six million media jobs.

The full story is at https://vaultify.snapwonders.com/our-story

May peace be with you,
Kenneth Springer

Licence

MIT — see LICENSE. The licence covers this server only; the snapWONDERS API it calls is proprietary.

來源:README.md,提交 2f558dc

工具

4

analyse_file

Run forensic analysis on a local image or video and return the per-file verdicts. Reports the A–F grade, what the metadata reveals (GPS, device fingerprint, encoder signatures), manipulation evidence, and any hidden content detected. **A null verdict means no answer, not a negative one.** Fields such as ``steganography_suspected`` come back ``null`` when that check produced no result — because it was skipped, or could not run on this file. Do not report a file as clean, unmodified or free of hidden content on the strength of a null; say the check did not return a verdict. Args: file_path: Path to a file on this machine. ``~`` and relative paths are fine. face_detection: Locate faces and return a count. On by default, matching the API. text_detection: Run OCR and return detected text. On by default, matching the API.

輸入參數file_path必填face_detectiontext_detection

hide_file

Hide a file inside a cover image or video, and save the result to disk. The output looks like an ordinary photo or video. Recovering the hidden file needs this exact password — it is not stored anywhere and cannot be reset, so make sure the user knows what it is before running this. Args: secret_path: The file to conceal. cover_path: The image or video that will carry it. password: Passphrase required to reveal it later. output_dir: Where to write the result. Defaults to alongside the cover file.

輸入參數password必填cover_path必填output_dirsecret_path必填

reveal_file

Extract content hidden inside an image or video, and save it to disk. Args: stego_path: The file believed to contain hidden content. password: The passphrase it was hidden with. output_dir: Where to write what is recovered. Defaults to alongside the input.

輸入參數password必填output_dirstego_path必填

convert_file

Convert a local image or video to another format, and save the output to disk. Args: file_path: The file to convert. output_format: Target format. Images: ``jpeg``, ``png``, ``webp``, ``avif``, ``heic``, ``jxl``. Videos: ``mp4h264``, ``mp4h265``, ``webm``, ``mkv``, ``mov``. output_dir: Where to write the converted file. Defaults to alongside the input.

輸入參數file_path必填output_diroutput_format必填

版本歷史

2
  1. v0.1.3最新Oct 22, 2026
  2. v0.1.2Oct 15, 2026

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