kino-mcp

MCP server that gives AI agents full access to video stream analysis, audio fingerprinting, quality monitoring, and encoding presets — powered by the kino-cli Rust binary.

Tools (8)

| Tool | Description | |------|-------------| | analyze_stream | Parse HLS/DASH manifest — renditions, codecs, duration, live status | | validate_stream | Check segment accessibility and bitrate conformance | | quality_check | Full QC report — DRM, captions, bitrate ladder | | monitor_stream | Live stream health check — latency, segment freshness | | fingerprint_audio | Generate audio fingerprint for content identification | | autotag_content | Auto-detect genre, mood, BPM from audio | | compare_streams | Diff two streams for quality mismatches | | encode_video | Generate encoding presets (mobile, desktop, 4k, low-bandwidth) |

Install

npm install -g kino-mcp

Requires kino-cli

# From source
cargo install --path crates/kino-cli

# Or from crates.io (when published)
cargo install kino-cli

If kino-cli is not in your PATH, set the KINO_CLI_PATH environment variable:

export KINO_CLI_PATH=/path/to/kino-cli

Configure in Claude Desktop

Add to your MCP settings (~/.claude/settings.json or Claude Desktop config):

{
  "mcpServers": {
    "kino": {
      "command": "kino-mcp",
      "env": {
        "KINO_CLI_PATH": "/path/to/kino-cli"
      }
    }
  }
}

Or if installed locally:

{
  "mcpServers": {
    "kino": {
      "command": "node",
      "args": ["/path/to/kino/mcp-server/index.js"]
    }
  }
}

Usage

Once configured, any MCP-compatible AI agent can:

• Analyze HLS/DASH streams to understand available renditions and codecs
• Validate segment accessibility before going live
• Run automated QC checks on video assets
• Monitor live stream health in real time
• Fingerprint audio for content identification and deduplication
• Auto-tag media files with genre, mood, and tempo
• Compare streams to detect quality regressions
• Generate encoding presets for target platforms

License

MIT