ffmpeg-mcp-lite vs memory
Side-by-side comparison to help you pick between these two MCP servers.
ffmpeg-mcp-lite by kevinwatt | memory by modelcontextprotocol | |
|---|---|---|
| Stars | ★ 24 | ★ 85,748 |
| 30d uses | — | — |
| Score | 46 | 77 |
| Official | — | ✓ |
| Categories | MediaDeveloper ToolsProductivity | Knowledge GraphAI / LLM ToolsProductivity |
| Language | Python | TypeScript |
| Last commit | this month | this month |
ffmpeg-mcp-lite · Summary
A feature-rich MCP server for video/audio processing using FFmpeg with tools for conversion, compression, trimming, and more.
memory · Summary
An MCP server implementing persistent memory using a local knowledge graph for AI models to remember user information across chats.
ffmpeg-mcp-lite · Use cases
- Automate video editing tasks through natural language commands in AI assistants
- Convert media formats without leaving your development environment
- Extract audio from videos for podcast creation or analysis
memory · Use cases
- Personalizing AI assistant interactions by remembering user preferences, history, and relationships
- Building context-aware chat applications that maintain conversation history
- Creating knowledge bases that persist across AI model sessions
ffmpeg-mcp-lite · Install
Prerequisites
Install FFmpeg on your system:
| Platform | Command | |----------|---------| | Windows | winget install FFmpeg | | macOS | brew install ffmpeg | | Linux | sudo apt install ffmpeg |
Installation
Add the following config to your MCP client:
{
"mcpServers": {
"ffmpeg": {
"command": "uvx",
"args": ["ffmpeg-mcp-lite"]
}
}
}Or install manually with:
pip install ffmpeg-mcp-liteClaude Desktop Configuration
Add to your claude_desktop_config.json:
{
"mcpServers": {
"ffmpeg": {
"command": "uvx",
"args": ["ffmpeg-mcp-lite"]
}
}
}memory · Install
Installation
Claude Desktop
Add to your claude_desktop_config.json:
{
"mcpServers": {
"memory": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/server-memory"
]
}
}
}VS Code
Use one-click installation buttons or manually configure in .vscode/mcp.json:
{
"servers": {
"memory": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/server-memory"
]
}
}
}Docker
{
"mcpServers": {
"memory": {
"command": "docker",
"args": ["run", "-i", "-v", "claude-memory:/app/dist", "--rm", "mcp/memory"]
}
}
}