Woof — See your Photo Gallery in your AI assistant
mcp-name: io.github.ouestcharlie/ouestcharlie-woof
Woof is the photo and video gallery companion to your your AI assistant (Claude Desktop, Goose, VS Code / GitHub Copilot...). It complements those powerful tools with a searchable gallery. Your photos and videos remain exactly where they are — on your own drives (local or mounted).
No cloud subscription. No proprietary lock-in. Your library, your way.
Woof is the MCP App frontend to "Où est Charlie ?" ("Where is Wally?" in French), a full AI native framework to manage your photos and videos.
What makes it different
Most photo managers lock your library into a cloud service (Google Photos, iCloud) or require a database server that becomes a single point of failure. Woof takes a different approach:
- Conversation as your gallery. Woof connects to your AI assistant (Claude Desktop, ChatGPT, Goose, VS Code / GitHub Copilot…) and turns it into a full photo browser. Ask in plain language, get results inline. No separate app to learn.
- Privacy by design. Only metadata travels to your AI assistant — your actual photos are served locally by Woof. Your pictures are never uploaded to any AI service unless you explicitly ask.
- No database lock-in. Metadata lives as XMP sidecar files right next to your photos, plus lightweight JSON manifests. Move a drive, copy a folder — your entire organization travels with your photos.
- Open formats, forever. XMP is an ISO standard. JSON is universal. AVIF is royalty-free. Every tool you already use — Lightroom, darktable, ExifTool — can read your metadata today and long after OuEstCharlie is gone.
- Your photos are never touched. Woof reads your library as-is. It never modifies, moves, or deletes your original files. It also honors existing XMP metadata from Lightroom, darktable, or any other tool — rather than overwriting it.
- Works with your existing folder structure. Just point Woof at your photos folder. No migration, no reorganization required.
More about OuEstCharlie and Woof on the OuEstCharlie Blog
Installation
Woof runs as a local MCP server. It connects to your AI desktop client (Claude Desktop, Goose...) and exposes your photo library as a set of tools.
Option A — Bundle install (recommended but Claude Desktop only)
Connect to Claude Desktop
Download the latest ouestcharlie-woof.mcpb from the Releases page and double-click it. Claude Desktop will prompt you to install Woof in one click — no configuration file to edit.
See also in Woof Blog:
Step by Step install of OuEstCharlie Woof in Claude Desktop
Option B — Manual uvx configuration
Prerequisites
Python packages of OuEstCharlie Woof are managed by uv and the command uvx. uv might be already available on your system.
System prerequisites (all install options):
- macOS:
brew install inih brotli gettext (required by pyexiv2 at runtime)
- Linux/Windows: no extra steps
Connect to Claude Desktop
Reference: Getting Started with Local MCP Servers on Claude Desktop
Open (or create) ~/Library/Application Support/Claude/claude_desktop_config.json and add or update mcpServers:
{
"mcpServers": {
"woof": {
"command": "uvx",
"args": ["--python", "3.13", "--from", "ouestcharlie-woof", "woof-bridge"]
}
}
}
Restart Claude Desktop. Woof will appear as an MCP integration, and the gallery will render as an interactive panel inside your conversation.
Connect to ChatGPT Desktop
NOTE: As of May 2026, ChatGPT is no longer supporting local MCP servers. Following is not longer available!
Connect to Goose
Reference: Goose MCP extensions documentation
Goose supports MCP servers via its extension system.
Either add through the user interface as a Custom Extension:
Setup Woof extension in Goose
Or add the following to your Goose configuration (~/.config/goose/config.yaml):
extensions:
woof:
type: stdio
cmd: uvx
args: ["--python", "3.13", "--from", "ouestcharlie-woof", "woof-bridge"]
enabled: true
Add to VS Code (Github Copilot harness)
To install in VS Code:
- From the command Palette (Ctrl+Shift+P or Cmd+Shift+P), select "MCP: Add Server..."
- Simplest is using "Pip Package" install option
- Type in the Woof package name: "ouestcharlie-woof"
- Accept to confirm
- The entry point is woof-bridge (not woof as proposed by the prompt)
The composed configuration should be:
{
"servers": {
"woof-bridge": {
"command": "uvx",
"args": [
"--python",
"3.13",
"--from",
"ouestcharlie-woof",
"woof-bridge"
],
"type": "stdio"
}
},
"inputs": []
}
Check if woof-bridge is activated through the "MCP: List Servers" from the Command Palette.
Other supported AI Assistants
Other clients support MCP Apps, for example Codex.
See the MCP Extension Support Matrix
Optional skill plugin
Woof provides optional skills with workflows, see the Tutorial section below. To install the plugin containing the skills, reference this repository as ouestcharlie/ouestcharlie-woof:
- Claude Desktop, from the Settings > "Plugins" > "Add" at the top-right corner > "Add a market place" > "Add from a repository"
- VSCode, from the Command Palette > "Chat: Install Plugin from Source"
First Steps
1. Register your photos folder
Once Woof is connected to your AI client, ask it to register your photo folder:
"Add a local library to Woof pointing to /Users/yourname/Pictures"
Woof supports any folder on a local drive — including folders synced from iCloud Drive, OneDrive, or Google Drive, as long as the files are locally available.
2. Index your library
Trigger the indexer to scan your photos and build the metadata index:
"Index my local library"
Woof will launch the indexing agent, which will:
- Read EXIF/XMP metadata from each photo
- Write XMP sidecar files alongside your originals (never modifying the originals)
- Generate thumbnails and previews
- Build a fast index for querying
Indexing speed is roughly 10 to 100 seconds per 1,000 photos depending on format and hardware.
3. Start browsing
Once indexing is complete, just ask:
"Show me photos in Woof from last July"
"In Woof, show me pictures taken near Paris"
"Search Woof for photos with 'Tour Eiffel' in the description"
"How many photos do I have in Woof?"
The gallery panel will appear inline in your conversation with matching results.
Ouestcharlie Woof photo gallery inside Claude Desktop
More tutorials
Storage
Woof supports local filesystem and cloud_mount libraries on macOS, Linux, and Windows:
- filsystem for a standard local hard drive or SSD, including local network drive (e.g. NAS)
- clound_mount for a folder synced from iCloud Drive, OneDrive, Google Drive, or Infomaniak kDrive — as long as files are downloaded and locally accessible
Native cloud storage (S3, Azure, GCS, OneDrive API) is planned.
Status
Woof is an early preview. It works well today for browsing and searching a local photo library.
Current features
| Feature | Notes |
|---|
| Compatible with Claude Desktop, Goose, VS Code | Any desktop application with MCP App support |
| Available on Macos, Windows, Linux | Python packages are built and released in Pypi |
| Local filesystem indexing | Files must be locally synced |
| Photos (JPEG, PNG, TIFF, HEIC, RAW) | HEIC and RAW depend on the build options |
| Video support (MOV, MP4) | |
| Gallery view as grid or preview | Photo details on preview |
| Image thumbnails and previews | Optimized for display |
| Search description, tags, rating, date, partition | full text search on description |
| Search photo features (date, dimensions, GPS bounding box) | |
| Search video features (duration, dimensions, GPS bounding box) | |
| Search camera features (make, model, aperture, lens) | |
| Sort ascending or descending on any field | |
| Change detection / automatic re-indexing | Partial — added and removed pictures |
Planned features
| Feature |
|---|
| Albums and smart filters |
| Share pictures with host (Claude Desktop, ChatGPT, Goose…) |
| Enrichment agents (faces, scene recognition) |
| Mobile companion app |
| Native cloud libraries (S3, OneDrive, GCS…) |
If you hit a bug or unexpected behavior, please open an issue.
Ouestcharlie Woof photo gallery inside VSCode, an alternative to Claude CoWork for techies
Privacy Policy
Woof is designed with privacy as a core principle.
- Data collected: Only photo metadata (EXIF, GPS coordinates, camera make/model, dates, file paths) is read and indexed. No account or personal information is collected.
- Data storage: All metadata is stored locally on your own device as XMP sidecar files and JSON manifests alongside your photos. No data is stored on any remote server.
- AI assistant: Only metadata and thumbnail images are sent to your AI assistant (Claude, ChatGPT, Goose…) when you perform a search. Your original photo files are never uploaded to any AI service unless you explicitly share them.
- Third parties: No metadata or usage data is shared with any third party.
- Retention: All data remains under your full control. Deleting the XMP sidecars and
.ouestcharlie/ folders from your photo library completely removes all Woof metadata.
For privacy questions, please open an issue.
Support
Bug reports and feature requests: GitHub Issues
Developers' corner
For developer and architecture documentation, see README_DEV.md.
### Contributing
See the Contributing section in OuEstCharlie
License
MIT license