snapWONDERS MCP (local)

com.snapwondersPublished by snapwonders.comv0.1.3Updated Oct 29, 2026

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

The publisher's own server: snapWONDERS Vaultify

VerifiedSTDIODesktop onlyFiles & StorageSecurity & MonitoringMedia & Design

Overview

AI-generated overview

Local MCP server that lets an assistant analyse, convert, hide files inside, and reveal files from images and videos on your own machine via snapWONDERS.

What you can do
  • Run forensic analysis on a local image or video: A–F grade, metadata exposure such as GPS and device fingerprints, manipulation evidence, hidden content, optional face detection and OCR
  • Hide a file inside a cover image or video and save the result to disk
  • Extract content hidden in an image or video with a passphrase and write it to disk
  • Convert images (jpeg, png, webp, avif, heic, jxl) and videos (mp4h264, mp4h265, webm, mkv, mov) to another format
When to use it
Useful when the files you want to inspect, convert or hide are on your own desktop and your client has no terminal, so a remote server could not reach them. Each tool completes a whole task and writes output back to your disk.
Requirements
Runs locally over stdio as a Python package (uvx or pip install snapwonders-mcp), desktop client only. Needs a snapWONDERS API key in the SNAPWONDERS_API_KEY environment variable from a free account with a verified email address. Network access to snapwonders.com over HTTPS is required because files are uploaded for processing.
Before you install
Files you point it at are uploaded to snapWONDERS for processing, so any readable path can be sent, including sensitive ones; check the path in each tool-approval prompt. The API key stays in the environment, but hide_file and reveal_file passphrases are tool arguments and may appear in model context, client logs and transcripts. Hide passphrases are never stored and cannot be reset, so losing one means the hidden file is unrecoverable. Tools write files to disk.

Installation

In SourceWeft

  1. Open snapWONDERS MCP (local) in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

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.

Source: README.md at commit 2f558dc

Tools

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.

Parametersfile_pathrequiredface_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.

Parameterspasswordrequiredcover_pathrequiredoutput_dirsecret_pathrequired

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.

Parameterspasswordrequiredoutput_dirstego_pathrequired

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.

Parametersfile_pathrequiredoutput_diroutput_formatrequired

Version history

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

Score

80% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 days25 pts
  • Auth declared10 pts

    Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.

  • Tools listedRequired15 pts
  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts

    Declare a license in the repository or the registry entry.

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