About Local Media Search MCP Server
Local Media Search MCP Server is an MCP server in the Search category: mCP server enabling AI agents to search across local media sources with MCP-compatible client integration. It has been installed 0 times through Conduid.
Install
git clone https://github.com/mugdhav/local_media_search_mcp_serverThis server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.
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README
title: Local AI Media Scout - Hackathon Space Submission emoji: 🎬 colorFrom: green colorTo: blue sdk: gradio sdk_version: "6.0.0" app_file: app.py pinned: false tags:
- building-mcp-track-consumer
- building-mcp-track-creative
🎬 Local AI Media Scout
Privacy-First Semantic Media Search MCP Server
100% Local & Private: Your media stays on your machine. AI runs locally. Zero cloud uploads.
🌟 Overview
Local AI Media Scout is a Model Context Protocol (MCP) server that gives AI assistants (like Claude) access to your local photos and videos through natural language search.
Unlike cloud-based solutions, this tool runs entirely on your local machine using the SigLIP AI model (2x faster than CLIP) to understand the content of your media files.
Perfect for:
- 🔍 Finding photos/videos using descriptions like "sunset at the beach" or "receipt for coffee"
- 🤖 Giving Claude Desktop "eyes" to see your local media library
- 🔒 Users who care about privacy and don't want to upload personal photos to the cloud
✨ Features
- Semantic Search: Search by meaning, not just filenames (e.g., "cat sleeping on sofa").
- Multi-Modal: Supports both Images (JPG, PNG, WEBP, etc.) and Videos (MP4, MOV, MKV, etc.).
- Privacy-First: All processing (indexing & searching) happens on your CPU/GPU.
- Dual Interface:
- 🔌 MCP Server: Connects to Claude Desktop.
- 🌐 Web UI: Built-in interface for testing and direct usage.
- High Performance: Uses
google/siglip-base-patch16-224and FAISS for fast indexing and retrieval.
🛠️ Installation
Prerequisites
- Python 3.10 or higher
- Git
1. Clone the Repository
git clone https://github.com/mugdhav/local_media_search_mcp_server.git
cd local_media_search_mcp_server
2. Create a Virtual Environment
It's recommended to use a virtual environment to manage dependencies.
Windows:
python -m venv venv
.\venv\Scripts\activate
macOS/Linux:
python3 -m venv venv
source venv/bin/activate
3. Install Dependencies
pip install -r requirements.txt
⚙️ Configuration
-
Create a
.envfile in the root directory (optional, defaults will be used):MEDIA_DIR=media INDEX_DIR=indexMEDIA_DIR: The folder containing your photos and videos (can be an absolute path).INDEX_DIR: Where the AI index files will be stored.
-
Add your media:
- Place your photos and videos in the
mediafolder (or whichever folder you configured). - Note: The first time you run the server, it will download the AI model (~150MB) and index your files. This may take a few minutes depending on your library size.
- Place your photos and videos in the
🚀 Usage
1. Start the Server
Run the application:
python app.py
You should see output indicating the server has started:
Web UI: http://localhost:7860
MCP Endpoint: http://localhost:7860/gradio_api/mcp/sse
2. Connect to Claude Desktop
To use this with Claude Desktop, you need to add the server configuration to your MCP settings file.
File Location:
- Windows:
%APPDATA%\Claude\claude_desktop_config.json - macOS:
~/Library/Application Support/Claude/claude_desktop_config.json
Configuration:
{
"mcpServers": {
"media-search": {
"url": "http://localhost:7860/gradio_api/mcp/sse"
}
}
}
Restart Claude Desktop after saving this file.
3. Using the Web UI
Open http://localhost:7860 in your browser to:
- Test search queries.
- View index statistics.
- Manually trigger a re-index.
- Inspect file details.
🤖 Available MCP Tools
When connected to Claude, you can use the following tools:
| Tool | Description |
|---|---|
semantic_search |
Search your media using natural language descriptions.Args: query (str), media_type (all/image/video), top_k (int) |
get_media_details |
Get metadata about a specific media file (size, type, path).Args: file_path (str) |
get_index_stats |
View statistics about your indexed library (count, size, etc.). |
reindex_media |
Force the server to re-scan your media directory.Args: force (bool) |
Example Prompts for Claude:
- "Find me pictures of my dog playing in the park."
- "Do I have any videos of the graduation ceremony?"
- "Show me the metadata for the first search result."
- "Reindex my media library, I just added some new photos."
🔧 Troubleshooting
- First Run Slowness: The first run downloads the SigLIP model. This is normal.
- Video Processing: Indexing videos takes longer as it extracts frames to understand the content.
- "File not found": Ensure your
MEDIA_DIRpath is correct in the.envfile. - MCP Connection Error: Make sure the server is running (
python app.py) before opening Claude Desktop.
📜 License
MIT License
Built for the MCP 1st Birthday Hackathon 🎂
README mirrored from the source repository 4 months ago. The original is authoritative.