MeshNodes

MeshNodes is a visual, node-based procedural mesh editor for Unity. Build complex geometry by connecting operation nodes in a graph — no mesh-processing code required.

Inspired by Shader Graph but built for geometry, MeshNodes gives you a fully non-destructive pipeline. Change any value anywhere in the graph and the entire mesh updates instantly. When you are happy with the result, one click bakes it as a real mesh asset directly into your project.

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Node Library — 30+ Nodes Included

Generate

• Primitive — cube, sphere, cylinder, capsule, plane, and more
• Custom Mesh — bring in your own base mesh

Combine

• Array — duplicate along an axis with spacing control
• Instances — place copies at arbitrary transforms
• Merge — combine any number of meshes into one
• Graph — nest an entire graph as a reusable compound node

Transform

• Translate, Rotate, Scale

Deform

• Bend, Hook, Inflate, Noise, Smooth, Spherify, Taper, Twist

Modify

• Bevel, Extrude, Filter Faces, Flip Normals, Subdivide

UVs

• UV Transform, UV Auto Fit

Vertex Color

• Color Node

Math / Variables

• Boolean, Integer, Float, Vector2, Vector3, Vector4, Math

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Key Features

Non-destructive workflow Every change propagates through the graph automatically. Nothing is baked until you decide.

Graph nesting Wrap any subgraph inside a Graph node and reuse it across projects like a function call.

One-click mesh baking Hit Build Mesh on the output node. The mesh is instantiated in the scene and saved to Assets/MeshNodes/Database/Meshes.

Custom node API Decorate any class with [MN_CustomNodeAttribute] and it appears under New Node / Custom in the context menu. Extend MeshNodes without touching the source.

Burst + Jobs acceleration The processing engine runs on Unity Jobs and Burst for fast procedural computation. A built-in validation tool (Tools / Mesh Nodes / Validation / Run Jobs Burst Parity + Perf) checks correctness and writes a performance report you can track over time.

AI / MCP integration MeshNodes includes a built-in Model Context Protocol server. Enable it from Tools > Mesh Nodes > MCP Server > Start Server, then point any MCP-compatible AI agent (Cursor, Claude, or others) at the Unity endpoint. Agents can create graphs, add and connect nodes, set properties, trigger recomputes, analyze meshes, and bake assets — all from a single prompt. A ready-to-use Cursor skill package (meshnodes-mcp/) is included.

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Getting Started

1. Open Tools > Launch Mesh Nodes
2. Right-click the canvas > Graph / New
3. Right-click > New Node / ... to add nodes
4. Connect outputs to inputs to define your pipeline
5. Click Build Mesh on the output node to bake

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Compatibility

• Unity 2022.3 LTS and later
• Built-in, URP, and HDRP compatible
• Editor-only package — baked meshes are standard Unity Mesh assets usable at runtime
• Burst/Jobs path requires the Collections package (Window > Package Manager > Unity Registry > Collections)

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Support & Community

• GitHub (bugs & feature requests): https://github.com/BadjanoEntertainment/MeshNodes
• Community forum: https://www.reddit.com/r/MeshNodes/
• Asset Store page: https://assetstore.unity.com/packages/tools/modeling/mesh-nodes-273635

Crypto AI Trader: Next-Gen Machine Learning Trading & Bot Operations Platform

A complete, self-hosted cryptocurrency trading platform that bridges deep learning price forecasting, real-time Binance execution, mobile Telegram interaction, and multi-client SaaS capability.

🚀 The Vision

In the highly volatile crypto market, manual trading is emotionally taxing, while typical algorithmic bots lack adaptability. Crypto AI Trader solves this by combining TensorFlow/Keras-based prediction models with a unified mobile interface (Telegram) and a local web operations dashboard (Orchestration Bridge).

Whether you want to run risk-free simulations in a sandbox, manage your own live funds via isolated margin, or orchestrate trading signals for multiple clients, this platform provides a secure, modular, and robust solution.

🌟 Key Pillars & Features

1. 🤖 Deep Learning Predictive Models

At the heart of the platform is a machine learning pipeline that processes real-time Binance market data to forecast market trends.

• Multi-Timeframe Feature Engineering: Models analyze technical indicators (RSI, oscillators, price volatility) across historical klines.
• Diverse Model Architectures: Supports multiple neural network versions including Dense chart models and LSTM (Long Short-Term Memory) networks for sequential time-series data.
• Auto-Rebalancing: The AI decision engine runs periodic cycles (evaluating positions every 5 minutes and running full strategy iterations every 30 minutes) to adjust leverage targets based on trend confidence and price momentum.
• Core Implementation: Check out the Trainer package and the neural network loading module bot.py.

2. 📈 Dual-Mode AI Trading Engine

Execute trades with precision and custom risk management in two distinct modes, operating under independent settings:

• Paper Trading (Sandbox): A simulated wallet starting with a virtual balance of 10,000 USDT to benchmark neural network performance, calculate fees, and monitor liquidations with zero risk.
• Live Trading: Real-time trade execution on Binance using isolated margin to maximize capital efficiency while strictly controlling downside risk.
• Safety Protocols: Integrates position watchdog timers, leverage limits (1x to 10x long, 1x to 2x short), daily loss caps, and circuit breakers that halt the bot in the event of persistent API connection drops.
• Core Implementation: Explore the AIBotService and the Binance integration client trader.py.

3. 💬 Telegram Command Center (Legacy)

The Telegram interface is now considered a legacy entry point, having been succeeded by the web-based administrative dashboard which offers significantly faster loading times and more precise data synchronization. While the web dashboard is the primary tool for platform management, Telegram remains fully operational as a convenience for users who wish to check status or execute quick commands without undergoing the standard web login process.

• Interactive Trading Flow: Place market, limit, or OCO (One-Cancels-Other) orders on the fly, with automated limit sells placed in profit-taking ratios upon order execution.
• Trade Signal OCR: Upload screenshots of trading charts or signals from other groups; the bot automatically extracts text, parses parameters, and initiates interactive trade confirmations.
• Real-time Notifications: Instant price alerts, news delisting notifications, and daily PnL summaries delivered straight to your chat.
• Core Implementation: See photo_handler.py for image parsing and the main entry point app.py.

4. 🎛️ Orchestration Bridge: Local Operations Dashboard

A self-hosted web console built for managing the bot on multi-cluster orchestration environments with Kubernetes and Docker.

• State Management: View and modify bot configurations (active symbols, leverage limits, notification preferences) and apply updates dynamically.
• Ops Command Center: Run remote services (systemd control), track logs (journalctl and deploy logs), and trigger secure git deployment pulls.
• Production-Grade Security: Bound locally by default and secured via HTTP Basic Auth, with production options for Cloudflare Tunneling, mandatory 2FA, and strict API rate limits.
• Core Implementation: Explore the FastAPI dashboard codebase in tools/orchestration_bridge/.

5. 👥 BotTrader: Client Copy-Trading SaaS

Turn your trading signals into a subscription service:

• Subscription Management: Clients subscribe to receive signals, with automated USDT/BTC deposit monitoring extending their subscription periods.
• Secure Client Key Storage: Clients input their API keys directly through Telegram. The bot immediately encrypts these keys at rest using an AES/RSA master key configuration and redacts them from log files.
• Managed Mirroring: Executes bot signals across client sub-accounts simultaneously with individual custom leverage ceilings.
• Core Implementation: Review routes/bottrader.py.

## 🛠️ The Tech Stack

• Programming Language: Python 3.8+ (type-hinted, modular structure)
• Machine Learning: TensorFlow / Keras (dense & LSTM models)
• Backend Frameworks: FastAPI (operations dashboard), python-telegram-bot (communication pipeline)
• Databases: SQLite (historical market klines and Telegram state), JSON/Pickle (bot settings and wallets)
• Data Sources: Binance WebSockets & REST API
• Security & Ops: systemd, Git hooks deployment, RSA encryption, Cloudflare Tunnels
• Dependency Injection: Unified AppContainer managing service lifecycles.

🔒 Security & Safety First

• Log Redaction: All incoming API keys or sensitive data are instantly redacted before writing to log files.
• Permission Hierarchy: Strictly separates command access (Owner/Admin, Authorized Traders, and BotTrader Clients) to prevent unauthorized trades or configurations.
• Local-First Architecture: Keeps your data and secrets on your own hardware, running under your control.

You will have access to free tier, that has basic information, but for the first ones I can gift some subscriptions in order to test those services

No service is currently live and actually need your binance token, its all beta with dry runs on trades, no actual trade is made

It is safe for testers, and safe for me

I will not disclose the website here, unless you guys approve it, I will have a commit for you to upvote if you want me to disclose here

I have gemini, antigravity, copilot, claude and cursor. I think cursor is the best and fastest, even though we probably have a lot less tokens compared to the model owners like claude or gemini.

Cursor has some questionable small llm models, but I was one of the lucky fellas that made anual subscription while their lowest tier of model was limitless, so on auto mode it will never run out.

Cursor is the fastest, because it uses more code than llm, other dumb agents like claude use llm for anything, while cursor try to use traditional things to manipulate data like regex.

Cursor might have less tokens for us to use, but it is more optimized to spend less.

There will always be the best LLM, but apparently other agents need to catch up to cursor asap.

These were all the takes I could figure out from using cursor against other CLI, please feel free to point out something wrong I said.

So I thought maybe I could check on you guys if you have any ideas on how to make something unique that would actually make VR more interesting then how it already is.

To be honest, I keep scrolling on Meta store and it all looks the same, and most of the games are not very polished.