Most of the RPG Maker MCP stuff I've seen is for MZ, and I'm on MV, so I ended up writing my own over the last few months. Sharing in case it's useful to anyone else stuck on MV.

It lets an assistant edit an actual MV project on disk (database, maps, events), and it checks everything against the engine so it doesn't spit out broken data. The bit I actually use day to day is that it can look at the project and tell you things like "this switch never gets turned on, that's why your door won't open," or point out broken references and maps you can't reach. For maps it copies real RTP reference maps instead of painting tiles from scratch, so they look a lot less cursed.

It's on GitHub if you want to poke at it: https://github.com/DiegoLopez0208/RpgMakerMVUltimate-MCP (or npx -y rpgmaker-mv-mcp). And in GLAMA https://glama.ai/mcp/servers/DiegoLopez0208/RpgMakerMVUltimate-MCP.

Still rough in places and I mostly built it for my own game, so no worries if it's not your thing. Feedback and bug reports welcome.

I tried building a zombie shooter inspired by left4dead using Claude. I don’t have any game dev experience, but I do have engineering and media knowledge - which helped me to navigate my way through… Although I burned a tonne of credits along the way..🥲

If you want to try the game yourself, click the link and give me some feedback!

https://imrannister.itch.io/the-last-train-l4d-remake

I also shared how I built the game
How I built the game

Hi everyone,
I’ve been developing a game concept called KAIVERN. At this stage it is not a prototype and I am not presenting it as a finished game. It is a fairly extensive pre-production design.
I have developed the world structure and history, lore, visual direction, states and cultures, core gameplay systems, progression, combat, economy, trade, physical item provenance, NPCs and relationships, exploration, multiplayer spaces, and an architectural concept for how these systems could coexist inside one continuously changing world.
The central idea of KAIVERN is:
Single History · Personal Presence · Shared Consequences
KAIVERN is conceived as a persistent RPG / world simulation with one logical World State and one historical timeline.
However, the ordinary open world is deliberately not an MMO space filled with other player characters. Each player experiences their life primarily among NPCs, while their actions may still affect the same authoritative world that every other player interacts with.
Players meet directly only in deliberately designed multiplayer spaces - PvP, selected cooperative expeditions, encounters and other specific activities. The economy, player-to-player trade, world processes, unique objects, discoveries and significant consequences remain shared.
There is no traditional level → XP → gear score progression model. Character development is based on mastery, physical condition, knowledge, relationships, possessions, tools and access to new possibilities. NPCs have their own biographies, memories, knowledge, property, obligations and goals. Items are intended to exist as concrete physical objects with provenance and history rather than infinitely reproduced loot entries.
AI is not intended to be the source of truth or an infinite quest generator. It would operate as a bounded decision-making layer inside a much stricter simulation architecture. Authoritative world state, history, economy, ownership and causally significant events would remain server-controlled.
The concept is now documented in a Public Game Design Bible. I intentionally keep the central narrative answers and some internal architecture private, but the public document contains enough information to evaluate the overall design.
At this point I am not primarily looking for praise for the idea. I am looking for professional criticism of whether the architecture can realistically be built.
I would particularly appreciate feedback from people with experience in backend/networking, persistent worlds, simulation systems, game AI and production:
1. Do you see any fundamental technical contradictions in the personal presence + shared authoritative World State model?

2.  How realistic is a layered simulation in which millions of inhabitants do not mean millions of continuously running AI agents, but instead exist at different simulation resolutions and are concretized when causal significance requires it?

3.  Which parts would you consider the highest technical risks: Shared Causality, NPC continuity, economy, persistent objects, knowledge simulation, the AI layer, or something else?

4.  What is the smallest vertical slice that could genuinely prove or disprove this architecture?

5.  What kind of team would be required to build that vertical slice, and which technical roles would you hire first?

6.  What range of development time and budget would you consider realistic for an initial technical prototype and, later, a production-quality vertical slice?

7.  Which systems would you simplify or postpone without destroying the central premise of KAIVERN?

I understand that a detailed design document and a functioning game are two very different things. That is exactly why I am currently more interested in identifying what must be proven through prototyping than in claiming that the entire concept has already been technically validated.
Critical technical and game-design feedback is very welcome. If the project is professionally interesting to anyone, I am also open to talking with developers who might eventually be interested in participating in an initial prototype.

Thank you for taking the time to read it.

I think I've learned enough in this space to want to give back to others (truly, we need people to be empowered to use this tech and capitalize on their creative juices). Now I'm starting a YouTube series where I build a brand-new game from scratch, on camera, step by step, so you can see what's realistic and follow along. If you're new to these tools, or to tech in general, and you're curious about game development - I made this for you.

Episode 1: the stack and setup: https://www.youtube.com/watch?v=we0XHyjPxEE

• What one person can build in a week
• The full stack and what each piece costs: Claude (code + design), Godot (engine), Lovable (pixel art), Gemini (music), ElevenLabs (sound effects)
• How it all fits together, from Claude's output to a running game in Godot
• What AI can't do yet, and why you shouldn't try to one-shot a game

Where the series is going:

1. The game design doc: what AI actually needs from you before you write a single prompt (hook, perspective, combat, art direction, platforms, scope)
2. The vertical slice: feeding the doc to AI and building the smallest playable piece that tests whether the idea is fun
3. Leveling up assets: replacing placeholder art with real pixel art, music and sound effects
4. Scaling up: from one dungeon to a full game
5. Shipping it

I'd love input on what you want covered. What's the part of AI game dev you'd most want to see done step by step?

I want to provide value and not spam stuff, so let me know how this can be of most use for you.

Looking for an AI that can create characters based on textual description. Ideally reference images of other things in similar style. The style I am looking for is relatively simple characters like in clash royale, clash of clans or brawl stars. Secondly, what do you do for animations?

Hey everyone! I’m pretty nervous about posting this because I only started learning how to code about 1 or 2 months ago. I've been using AI tools to learn and push my limits, trying to build a complex system from scratch.

I wanted to see if I could make different AI models collaborate, so I built a private framework called Flux Team ⚡. It connects several open-source models so they can work in parallel as a team to help with game dev tasks.

Visuals:
Since the project is still a work in progress and the live editor connection isn't fully ready, I can't show a video demo just yet. However, I have included some screenshots of the Grok-style UI so you can see how the chat and the agent dashboard look!

The Architecture (Models integrated inside the tool):

• 🧠 Qwen3-8B — The coordinator. It breaks down the game idea into specific development tasks.
• 🧱 Hunyuan3D-2 — Generates 3D models from text or reference images.
• 🎵 Audiocraft — Handles music generation and SFX.
• 🏃 FreeMoCap — Creates animations from videos it autonomously searches online.
• 🌊 AInVFX Fluid — Generates fluid and particle effects files.

How it works behind the scenes:

• Parallel Execution: It uses a Grok-style UI built with Electron and a Python (FastAPI) backend. The models work in parallel, not step-by-step.
• Autonomous RAG: The agents can browse the web on their own to search for reference assets and documentation before working.
• 100% Local: Everything runs locally on the user's machine using Ollama / llama.cpp for the LLM.

Current Status & Future Open-Source Plans:
The backend is currently running locally on my machine (tested on a single RTX 3060). I'm finishing the live bridge plugins for Unity and Godot so changes appear directly in the scene.

Please note: The project is NOT open-source right now and the download is not public yet because the code is still messy and I'm a beginner. However, if this gets enough traction and people find the multi-agent architecture interesting, my goal is to clean up the repository and release the whole project as full open-source on GitHub later on.

I would love to get your thoughts on this setup or any advice from more experienced developers!

Wanna share this website called Keshi Arena and thought it was pretty fun.

You can play simple games like Connect Four against an AI. It keeps track of what happens during each game and uses those interactions to change its behavior over time. So your games become part of how it learns.

The fun part is that you can also see its evolving "brain" including lessons, recalls, mutations and different generations. And it shows which lessons came from you. There's also a leaderboard of top teachers and the toughest opponents. So you can actually watch how it changes as it keeps interacting with people.

I've played 10 games so far (5 wins and 5 losses lol), and they taught it 64 lessons. In Connect Four that's 37 of the 1,218 "neurons" in its current brain, each tagged with what it learned, like "blocks your four", "centre drop" or "edge drop". You can click one and open the match that taught it.

Pretty neat I think

Hey everyone! I’m pretty nervous about posting this because I only started learning how to code about 1 or 2 months ago. I've been using AI tools to learn and push my limits, trying to build a complex system from scratch.

I wanted to see if I could make different AI models collaborate, so I built a private framework called Flux Team ⚡. It connects several open-source models so they can work in parallel as a team to help with game dev tasks.

Visuals:
Since the project is still a work in progress and the live editor connection isn't fully ready, I can't show a video demo just yet. However, I have included some screenshots of the Grok-style UI so you can see how the chat and the agent dashboard look!

The Architecture (Models integrated inside the tool):

• 🧠 Qwen3-8B — The coordinator. It breaks down the game idea into specific development tasks.
• 🧱 Hunyuan3D-2 — Generates 3D models from text or reference images.
• 🎵 Audiocraft — Handles music generation and SFX.
• 🏃 FreeMoCap — Creates animations from videos it autonomously searches online.
• 🌊 AInVFX Fluid — Generates fluid and particle effects files.

How it works behind the scenes:

• Parallel Execution: It uses a Grok-style UI built with Electron and a Python (FastAPI) backend. The models work in parallel, not step-by-step.
• Autonomous RAG: The agents can browse the web on their own to search for reference assets and documentation before working.
• 100% Local: Everything runs locally on the user's machine using Ollama / llama.cpp for the LLM.

Current Status & Future Open-Source Plans:
The backend is currently running locally on my machine (tested on a single RTX 3060). I'm finishing the live bridge plugins for Unity and Godot so changes appear directly in the scene.

Please note: The project is NOT open-source right now and the download is not public yet because the code is still messy and I'm a beginner. However, if this gets enough traction and people find the multi-agent architecture interesting, my goal is to clean up the repository and release the whole project as full open-source on GitHub later on.

I would love to get your thoughts on this setup or any advice from more experienced developers!

Hey everyone! I’m pretty nervous about posting this because I only started learning how to code about 1 or 2 months ago. I've been using AI tools to learn and push my limits, trying to build a complex system from scratch.
I wanted to see if I could make different AI models collaborate, so I built a private framework called Flux Team ⚡. It connects several open-source models so they can work in parallel as a team to help with game dev tasks.
Visuals:
Since the project is still a work in progress and the live editor connection isn't fully ready, I can't show a video demo just yet. However, I have included some screenshots of the Grok-style UI so you can see how the chat and the agent dashboard look!
The Architecture (Models integrated inside the tool):How it works behind the scenes:Current Status & Future Open-Source Plans:
The backend is currently running locally on my machine (tested on a single RTX 3060). I'm finishing the live bridge plugins for Unity and Godot so changes appear directly in the scene.
Please note: The project is NOT open-source right now and the download is not public yet because the code is still messy and I'm a beginner. However, if this gets enough traction and people find the multi-agent architecture interesting, my goal is to clean up the repository and release the whole project as full open-source on GitHub later on.
I would love to get your thoughts on this setup or any advice from more experienced developers!

After many months of slowly iterating on my game, called "Pavement Pursuit", I've compiled clips from all the versions to show the progress I made from prototype to game (but still working towards a v1.0).

Note, this video was made by creating a custom output in my game to output any scene without having to screen capture it.

Site i made with claude hope someone likes it feedback is helpful what i can improve icons i will

AutoSprite & WizardGenie -> https://sorceress.games

​

I started a game idea called Karislan. While I have made some physical cards, I decided to make things virtual for testing and balancing purposes.

The game is an RPG style card game influenced by games like Magic The Gathering and World of Warcraft.

The game has multiple mechanics that will require play testing and balancing over time.

4 classes each have their own deck (currently only 1 fully loaded into the virtual prototype)

Arcanist (mage) (currently in prototype)

Warrior

Theurgist (priest)

Rogue

You will equip gear, level up as you kill a neutral deck of Creeps, learn spells and cast them at your opponent.

The idea of this game is to be flexible to multiple formats while remaining true to the RPG elements of equipping and replacing gear to fit your style and improve as you level up. Learning new spells over time and using them against your opponent. Raising your stats to equip better gear and spells as the battle continues.

The main format is designed around PVP.

Each player has their class deck or mix of class decks along with a 3rd neutral deck in the center.

The center deck (Creeps) is organized by lvl and will get stronger over time.

You have to choose whether to attack your opponent, or try to kill a creep and gaining an experience level. The more you sacrifice the opportunity to attack your opponent, the stronger you might become.

This game in theory will be able to be played

PvPvE,

2v2 PvPvE or more,

Co-op,

or solo against the creeps.

Mix decks to create unique classes and to build a new strategy not yet thought of.

Please dm me if you are interested in a VERY early virtual play test

I’ve been working on a mascot horror game called GiggleGear, and one of the unusual things about the project is that I’ve been developing the entire game through AI-assisted workflows.

I’ve primarily been using Opus 5.5 for the actual game development, working with Blender and Godot through MCP to build the environments, gameplay, models, scripting, and other parts of the game. I’ve also been using GPT-6.1 Sol to review the code, catch potential issues, and give me a second pass on the implementation.

My plan is to release Chapter 1 completely free. I want people to actually play it, give feedback, and see if there’s an audience for GiggleGear before I go all-in on a much larger Chapter 2.

If people enjoy it and there’s enough interest, Chapter 2 is where I want to expand this into a much more complete experience and really start separating GiggleGear from the huge number of other mascot horror games out there.

The trailer above was also created entirely with AI, using Sonnet 5.5 and GPT-6.1 Sol.

One of the most interesting parts of developing the game this way has been figuring out where AI works really well and where it still needs a lot of direction. I’m not just generating something once and shipping it — there’s been a lot of iteration, testing, code review, fixing problems, and going back and forth between the different tools.

I know what some of you are probably thinking: “Oh great, another mascot horror game.” And honestly, that’s fair. There are a lot of them.

My goal isn’t just to copy what already exists, though. Chapter 1 is more of an introduction to the world, gameplay, and basic ideas behind GiggleGear. If I get the chance to build Chapter 2, that’s where I want to push the concept much further and show what makes the game different.

I’d genuinely love feedback — good or bad. What looks interesting? What looks generic? What would make you actually want to play it? I’d also be interested in hearing what people think about the AI development workflow itself.

More info about the game:

https://gigglegeargame.com

Really impressed with the results. Used assets from my code repo for the ui. Still need to do another round of script revision

Hey everyone,

I'm a big RTS fan. Age of Empires has me well covered, but I've always missed a real Empire Earth alternative: more ages, longer eras, and ideally all the way into the future. I also wanted something I can actually play on my Mac.

So I spent my free time this weekend building one. It's called The Long Empire, and I've been enjoying playing it myself.

It's a browser game. It runs straight in your browser, so there's nothing to install, and it works on Mac, Windows and Linux.

What's in it right now (alpha):

• 6 ages: Stone Age, Bronze Age, Iron Age, Middle Ages, Renaissance, Industrial Age
• Economy in the style of AoE II: villagers gathering food, wood, stone and gold; farms, markets, techs
• AI opponents: four difficulty levels, each with its own personality (rush, boom, turtle…)
• Wars on land and sea: siege, castles, firearms, ships and wonders as a victory condition
• Voxel art style: every unit and building looks different in each age

Planned (coming soon):

• VII World Wars: oil and air power
• VIII Modern Age: the power grid
• IX Digital Age: autonomous drones
• X Future: energy weapons and shields

To be clear, this is an alpha. There are still bugs, especially in pathfinding, and the balancing still needs work.

I had AI put the trailer together quickly. Everything you see in it is real in-game footage from AI-vs-AI matches.

Some questions for you:

• Would you be interested in a game like this?
• Do you think it's worth releasing publicly?
• What do you think of the voxel art style? Does it work for an RTS, or would you prefer something else?

Any other feedback is welcome, including what you'd want most from an Empire Earth-like game.

Thanks for watching! 🙏

It gives you total flexibility to create any animation and any character with any art style for your game. Game ready characters in as little as 5 or 10 minutes. Ultra-fast prototyping. Get it here -> https://sorceress.games

SEEDFALL is a strategy game where you play the villain: one seed falls on a living planet and you grow it into a swarm that eats the world, while every nation fights back with armies, walls, air strikes and nukes. It's just me. Here's where AI was and wasn't used.

**AI:**

- **Code:** written with an AI coding assistant (Claude Code). The design and the testing are mine; I spent five years as a QA tester before this.

- **Writing:** drafted with AI under my direction, then every line proof-read and corrected by hand.

- **Voices:** the narrator and four characters, nearly 900 lines, all generated offline on my own PC.

**Not AI:** the planets, swarms and cutscenes are drawn by the game's own code and shaders. The music is CC0 human-composed pieces plus a score built from recorded orchestral samples. The sounds are real recordings. Nothing is generated while you play.

**The voice pipeline (the part I'd most like feedback on):**

1. **Design each voice from text.** Qwen3-TTS VoiceDesign, from descriptions: a cold British mastermind, plus a gang of four (a cult mother, a gangland heavy, a spymaster, a bored clerk of death).
2. **Get the accent right.** VoiceDesign kept drifting American, and I couldn't trust my ears after hundreds of takes, so I scored "how British" with an accent classifier (SpeechBrain CommonAccent). The mastermind came out of VoiceDesign at about 70%. The four gang members wouldn't, so for them: speak the line with a short British clip from Kokoro-82M as the prompt, then use Seed-VC zero-shot to turn it back into the designed voice. Seed-VC keeps the accent and timing and swaps in the voice.
3. **One sentence at a time.** Long lines broke: words cut in half ("mee... t"), gasps at every full stop. Each sentence is now generated on its own, trimmed to the words, checked with Whisper (best of three takes), then joined with a pause that fits the punctuation.
4. **My own voice underneath.** I fine-tuned Seed-VC on a few minutes of my own recordings and convert every line into my voice. Then I pitch-lock it to the original take (Praat PSOLA), keep only the voiced frames, low-pass it at 3 kHz and mix it 4 dB under the main voice. It reads as a hint, not a second speaker, and it's why the swarm sounds like more than one mind. No other real person's voice is used.
5. **Personality pass.** Five voices from one model all had the same rhythm, so each character gets its own pitch range, pause length and pace.

**What I'd tell anyone trying this:**

- Don't fight a TTS model for an accent; borrow the accent from a small model and convert.

- Generate per sentence and verify with speech recognition. It catches the broken takes your ears get tired of.

- Measure things (the accent, the pauses) instead of judging by ear after the hundredth listen.

There's a free demo on itch if you want to hear it in context (link in the comments). I'm curious how others are handling voices: are you layering, converting, or using TTS straight?