Godot Engine
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The game engine you waited for... Godot provides a huge set of common tools, so you can just focus on making your game without reinventing the wheel.
Godot is completely free and open-source under the very permissive MIT license. No strings attached, no royalties, nothing. Your game is yours, down to the last line of engine code.
DevPerform is engineering intelligence for engineering leaders: delivery metrics and developer sentiment in one product, so when a number moves you can ask the team about it and see both answers side by side.
Connect GitHub, GitLab, or Bitbucket and DevPerform computes DORA metrics, phased cycle time, review health, throughput, and investment allocation automatically โ no agents on developer machines, no CI changes, and your source code is never stored. Anonymous developer surveys (DX Core 4, eNPS, engagement) roll into a 0โ100 Experience Index you can trend wave over wave, and survey results can be triaged into team-visible focus areas with follow-through tracking.
It is deliberately not a surveillance tool: there are no individual rankings or leaderboards, survey answers sit behind an anonymity threshold, and AI adoption and impact are measured at team level only.
Fully self-serve: instant interactive demo, free public repo benchmark, public pricing, free tier, and a 14-day Pro trial. No sales call required.
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DevPerform's answer:
Engineering leaders โ VPs, directors, and team leads โ at software teams of any size, from a small startup to a large enterprise. DevPerform is self-serve, so small teams can start in minutes, and it scales to large orgs and monorepos without agents or CI changes. Any company building software on GitHub, GitLab, or Bitbucket is a fit.
DevPerform's answer:
DevPerform was built by engineers who kept seeing the same gap: delivery dashboards that flag a slow week but can't explain it, and engagement surveys nobody acts on. Putting the two in one loop โ number moves, team explains, leadership commits, next survey shows the follow-through โ turned out to be the product. Launched in 2026, bootstrapped and self-serve from day one.
DevPerform's answer:
DevPerform pairs delivery metrics (DORA, cycle time, review health) with anonymous developer surveys in one product. Metrics tell you what is slow; surveys tell you why โ and when a number moves you see both side by side, then close the loop: mark a survey dimension as a focus area, set a goal on it, and the next wave shows whether it worked.
DevPerform's answer:
It's self-serve end to end where most of this category is sales-led: an instant demo with no signup, a free public repo benchmark, public pricing from $0, and a 14-day Pro trial with no credit card. Setup reads your GitHub, GitLab, or Bitbucket metadata directly โ no agents on developer machines, no CI changes โ and everything ships on two public tiers with no seat minimums or annual-only contracts.
DevPerform's answer:
React + TypeScript frontend, Python (FastAPI) backend, PostgreSQL, deployed on Kubernetes. Data comes from the GitHub, GitLab, and Bitbucket APIs โ repository metadata only; source code is never stored.
Based on our record, Godot Engine seems to be more popular. It has been mentiond 479 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Godot โ open-source game engine with great audio support. - Source: dev.to / 3 months ago
Open source engines like Godot reduce the barrier. Zero licensing cost, a 50MB download, and a growing community of over 102,000 GitHub stars. AI tools like Ziva that generate engine-specific code can cut prototype time further. - Source: dev.to / 4 months ago
In Godot, you do not create a PlayerCharacter class that extends Character that extends Entity. You compose a player from independent nodes:. - Source: dev.to / 4 months ago
For game engines, Godot was too young, Unity just released a statement to make the developers give them more money, so we were left with Unreal Engine. - Source: dev.to / 4 months ago
So much incorrect and misinformation in these comments. As someone who is building an agent[0] with MCP tools, neither the MCP tool description nor the response is the problem. Both of those are easily solved by not bloating them. The real killer is the input tokens on each step. If you have 100k tokens in the conversation, and the LLM calls an MCP tool, the output and the existing conversation is sent... - Source: Hacker News / 5 months ago
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