PROJECT: KINO
SPECIFICATION DOCUMENT - VER 1.0

Kino: Video Intelligence for AI Agents

The first formally verified, Rust-native video infrastructure designed for the Model Context Protocol (MCP).

▣ Purple Squirrel Media LLC
⚙ Rust 2021 Edition
↦ 14K LOC
AMPLITUDE (dB) 4500kbps FRAME_RATE CODEC_PIPELINE MCP COMPATIBILITY LAYER NEURAL NET INTERFACE 0xAFE608EE$
PROJECT: AI-VIDEO INTEGRATION ANALYSIS
DRAWING NO: AI-VB-000
SCALE: NTS
DATE: FEB 25, 2026
AI Agents are Video-Blind

Text & Image Processing

Latency< 100ms
Data extractionStructured
ProcessingInstant

Video Processing (Current State)

Latency> 30s
Data extractionBlocked
ProcessingBottleneck
Inter TightTemporal Reasoning Gap

The Blind Spot

LLMs cannot inherently reason about temporal media streams or audio time-series data.

Inter TightWrapper Limitations

The Bottleneck

Current wrappers (FFmpeg/Python) are slow, memory-unsafe, and lack structured reasoning.

Inter TightQuality Assurance Failure

The Result

Hallucinations on content and inability to perform basic QA tasks.

PROJECT: AI-VIDEO INTEGRATION ANALYSIS
DRAWING NO: AI-VB-001
SCALE: NTS
DATE: FEB 25, 2026
Giving Agents Eyes and Ears

Raw Streams

▶ HLS
□ DASH
▶ MP4
➞

Kino MCP Server

  • Real-time Analysis
  • Fingerprinting
  • QC Checks
The Engine
➞

Structured Intelligence

{
  'codec': 'h264',
  'fps': 30,
  'genre': 'Jazz',
  'issues': []
}
Kino translates raw video/audio into actionable data that agents (Claude, GPT) understand instantly.
PROJECT: AI-VIDEO INTEGRATION ANALYSIS
DRAWING NO: AI-VB-002
SCALE: NTS
DATE: FEB 25, 2026
Built for Speed, Safety, and Modularity

7-Crate Workspace

kino-cli14 subcommands
kino-mcp8 MCP tools
kino-wasmbrowser target
kino-coreHLS/DASH/ABR/DRM
kino-frequencyFFT engine
kino-desktopGStreamer
kino-pythonPyO3 bindings
kino-tauricross-platform

Engineering Specs

Total Size:
14K LOC
Architecture:
Zero-copy hot paths
Runtime:
Async Tokio
Safety:
100% Safe Rust
(No 'unsafe' blocks in core)
Parser:
Nom combinators
Crypto:
Ring (DRM)
PROJECT: AI-VIDEO INTEGRATION ANALYSIS
DRAWING NO: AI-VB-003
SCALE: NTS
DATE: FEB 25, 2026
Defensible Engineering

Performance

[LATENCY OPTIMIZATION]   [RESOURCE EFFICIENCY]
⏱

Rust-native execution. 4ms startup time vs. Python overhead. Zero memory leaks.

Correctness

[FORMAL SPECIFICATION]   [LOGICAL VALIDATION]
✓

TLA+ Formal Verification. Critical state machines are mathematically proven, not just tested.

Integration

[MODULAR INTERFACE]   [ECOSYSTEM COMPATIBILITY]
❖

MCP-Native. Day 1 compatibility with Claude, OpenAI, and custom agents.

PROJECT: AI-VIDEO INTEGRATION ANALYSIS
DRAWING NO: AI-VB-004
SCALE: NTS
DATE: FEB 25, 2026
VARIABLE state, bufferLevel Init == state = "Idl /\ bufferLevel = 0 Next == \/ (state = "Idle" state' = "Buff state' = "Init state' = "Buff bufferLevel = 0 bufferLevel = 0 ) == \/ (state = "Idle" /\ state' = "Buffering") \/ (state = "Idle" /\ state' = "Buffering") rLevel = 10 t, bufferLevel = 0) /\ bufferLevel) { state = bufferLevel }
Mathematical Proof of Correctness

Verified Invariants (25+)

PSMPlayerState: Models 9 lifecycle states (Idle to Error).
PSMAbrAlgorithm: Proves ABR switching never oscillates below quality thresholds.
PSMDrm: Verifies handshake correctness.
PSMBufferController: Buffer never underflows during playback.
PSMConcurrentStreaming: Multi-stream coordination is deadlock-free.
“We didn’t just write code; we proved it works.”
PROJECT: AI-VIDEO INTEGRATION ANALYSIS
DRAWING NO: AI-VB-005
SCALE: NTS
DATE: FEB 25, 2026
Shazam for Agents
RustFFT (100x Realtime) ↓

Fingerprinting:

SHA-256 hashes of spectral peak constellations.

Auto-Tagging:

AI detection of Genre, Mood, and BPM via spectral centroids.

Identification:

Detects duplicate content and rights management.

PROJECT: AI-VIDEO INTEGRATION ANALYSIS
DRAWING NO: AI-VB-006
SCALE: NTS
DATE: FEB 25, 2026
Native Fluency in Agent-Speak

Available Tools

analyze_stream
validate_stream
fingerprint_audio
quality_check
monitor_stream
autotag_content
compare_streams
encode_video

Agent Response

{
  "tool_use": "quality_check",
  "result": {
    "status": "pass",
    "resolution": "1920x1080",
    "bitrate_ladder": [
      "320p",
      "720p",
      "1080p"
    ],
    "drm": "Widevine"
  }
}
Agents call tools natively to receive structured data—no CLI required.
PROJECT: AI-VIDEO INTEGRATION ANALYSIS
DRAWING NO: AI-VB-007
SCALE: NTS
DATE: FEB 25, 2026
Battle-Tested Infrastructure
[PASS] Mux HLS Parsing : Successfully parsed multi-rendition manifests (320p to 1080p).
[PASS] Segment Validation : Verified accessibility of encrypted segments.
[PASS] DRM Handshake : Validated Widevine and FairPlay signals.
[PASS] Performance : 4ms startup time. Zero memory leaks detected.
✓ v1.0.0 STABLE
PROJECT: AI-VIDEO INTEGRATION ANALYSIS
DRAWING NO: AI-VB-008
SCALE: NTS
DATE: FEB 25, 2026
Unlocking Autonomous Media Workflows
🛡

Content Moderation

Real-time policy checking and audio fingerprinting on live streams.

⚙

QA Bots

24/7 automated validation of bitrate ladders and DRM compliance.

🏷

Auto-Indexing

Tagging libraries by mood/genre without human intervention.

⚡

Edge Compute

Running analysis in-browser via WASM (Cloudflare Workers compatible).

PROJECT: AI-VIDEO INTEGRATION ANALYSIS
DRAWING NO: AI-VB-009
SCALE: NTS
DATE: FEB 25, 2026
Every AI Company is a Media Company
LLMs &
Agents
Video
Infrastructure
The
Void

Multimodal Shift

Models must ingest and reason about video programmatically.

The Missing Standard

There is no 'Video Standard Library' for AI agents—until Kino.

Opportunity

Kino is the standard interface between LLMs and Video.

PROJECT: AI-VIDEO INTEGRATION ANALYSIS
DRAWING NO: AI-VB-010
SCALE: NTS
DATE: FEB 25, 2026
Strategic Fit & Integration

AI Labs

(Anthropic / OpenAI)

Give models native, verified video capabilities immediately.

⚙
KINO Core

Video Infra

(Mux / Cloudflare)

Offer “Agent-ready” APIs to customers.

Media Tools

(Adobe / Frame.io)

Embed reliable, automated analysis into creative workflows.

PROJECT: AI-VIDEO INTEGRATION ANALYSIS
DRAWING NO: AI-VB-011
SCALE: NTS
DATE: FEB 25, 2026
Accelerate Your Video Roadmap by Years
Timeline A:
Build In-House
Hire Rust Team → Build Core → Write TLA+ → Debug → Release
24 Months (High Risk)
Timeline B:
Integrate Kino
Acquire & Plug-in
Immediate (Verified)
Offer: Acquire the IP, the formally verified TLA+ specs, and the “first-mover” advantage in MCP video tooling.
PROJECT: AI-VIDEO INTEGRATION ANALYSIS
DRAWING NO: AI-VB-012
SCALE: NTS
DATE: FEB 25, 2026
Technical Specifications

License

Dual Licensed: MIT / Apache-2.0

Core Dependencies

  • Tokio (Async Runtime)
  • Symphonia (Audio Decoding)
  • Ring (Crypto/DRM)
  • Nom (Parser Combinators)

Deployment Targets

  • Native Binary (Linux/macOS/Windows)
  • WASM (WebAssembly)
  • Python (PyO3 bindings)
  • Docker Container

Hardware Acceleration

VA-API, VideoToolbox, NVDEC auto-detection.

PROJECT: AI-VIDEO INTEGRATION ANALYSIS
DRAWING NO: AI-VB-013
SCALE: NTS
DATE: FEB 25, 2026
⦿
Let's Build the Eyes of AGI.
Ready for integration today.
Purple Squirrel Media GitHub Repository Documentation Demo
$ npm install -g kino-mcp
PROJECT: AI-VIDEO INTEGRATION ANALYSIS
DRAWING NO: AI-VB-014
SCALE: NTS
DATE: FEB 25, 2026