GitHub
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
作者提供的说明(英文原文)
Edit-settle-verify loop, observe, replay and log tools for AI agents working in the Unity Editor
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"playcal": {
"command": "uvx",
"args": [
"playcal",
"mcp"
]
}
}
}在终端中运行这条命令
claude mcp add playcal -- uvx playcal mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"playcal": {
"command": "uvx",
"args": [
"playcal",
"mcp"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"playcal": {
"type": "stdio",
"command": "uvx",
"args": [
"playcal",
"mcp"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日
注册名称已通过 GitHub 账户 RizgarOzan 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(0.2.1)于今天进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。
同一分类中有:GitHub, Desktop Commander, Cloudflare MCP
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
MCP server for terminal commands, file operations, and process management
Cloudflare MCP servers
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
One open-source toolkit for AI agents that build games. It gives your agent a loop it can trust (edit → wait until the editor has really settled → check the change actually landed → look only at what changed → assert), and it checks bot playtests against real players: *"the bot finds level 12 easy, but people will pass it about 41% of the time (CI 30–53%)."*
Unity first, built on top of Unity's official CLI. Godot works too (headless, through a probe script). Unreal is postponed, see the table below.
*AI agents: read llms.txt first.*
Status: pre-alpha (v0.1.0). Today the event schema,
ingest,report,calibrate,logs,loop,query,snap,observe,replay,baseline(perf and memory),visual,tests,affected,lock,meta,checkpoint,doctor, the MCP server and the Unity SDK work;loop,query,snap,observe,replayand the SDK frame recorder were checked on a live Unity 6000.3 Editor. Everything below marked *planned* isn't built yet. I'd rather show a short honest list than a long fake one. Progress is tracked in the roadmap.
*A real run on a live Unity 6000.3 Editor: the text is what playcal printed, and the waits are sped up (their real length is shown).*
Agents working in a game editor fail in boring, repeatable ways:
Unity's official CLI and the community MCP servers give you the building blocks: play, test, capture, console. Nothing ties them into a loop that handles these failures. playcal is that loop, plus scene diffs that survive an Editor restart, perf and screenshot gates, flaky-test quarantine, and calibration against human players. See the benchmark for what the loop does and doesn't buy you on a live Editor.
Requires Python 3.10+.
pipx install playcal
playcal modules
For the latest main, use pipx install git+https://github.com/RizgarOzan/playcal. The Unity SDK installs from a git URL, see Unity SDK.
Paste this into Claude Code, Cursor, Codex or any agent with a shell:
Install playcal for this project:
Do not change project files yet.
playcal mcp is a stdio MCP server. Every module becomes a tool (playcal_ingest, playcal_logs, playcal_loop, ...), built from the same argument definitions as the CLI, so the two can't drift apart.
The server's initialize reply carries a short "which command when" guide as MCP instructions, the same lines that open the skill file, so an agent knows to run doctor first and to put Editor writes through loop.
# or pick it from the MCP Registry as io.github.RizgarOzan/playcal
claude mcp add --transport stdio playcal -- playcal mcp code --add-mcp '{"name":"playcal","type":"stdio","command":"playcal","args":["mcp"]}'
If your agent has a shell, a skill file is cheaper than MCP (no tool list in every prompt):
mkdir -p .claude/skills/playcal && playcal skill > .claude/skills/playcal/SKILL.md
Or get both at once. In Claude Code, the plugin adds the skill and the MCP server (it starts the server with pipx run playcal mcp):
/plugin marketplace add RizgarOzan/playcal
/plugin install playcal@playcal
For other agents, skills.sh installs the same skill file:
npx skills add RizgarOzan/playcal
playcal skill --project . writes .claude/skills/playcal/SKILL.md into a game project. It spots the engine (Unity: Assets/ + ProjectSettings/, Godot: project.godot) and puts the red gate first: the settle and observe commands that must pass before a change counts as done. In a test, a fresh Claude Code session given only "add a print to main.gd" in the Godot sample loaded the skill and ran loop settle --engine godot without being asked (it checked the print with plain Godot instead of observe).
Every command can print --json, so agents can read the result without scraping text.
playcal ingest (works today)This command validates gameplay events against schema/event-v0.json. It accepts JSONL files, or free text that contains PC0: blobs. The in-game "send result" button produces those blobs, and players can paste them into any chat.
playcal ingest sessions.jsonl --json
playcal ingest whatsapp-export.txt --paste
Valid events go to accepted.jsonl. Every line that fails goes to rejected.jsonl with the reason.
The schema doesn't accept unknown fields, so names, emails, device IDs, location and IP can't slip in. See PRIVACY.md.
playcal report (works today)Per-level pass rates, counted two ways: per player and per attempt. Each rate comes with a 95% Wilson interval, because with 10 players a single "60%" means very little.
playcal report accepted.jsonl
playcal report accepted.jsonl --json
Different game_versions stay separate, and levels sort naturally (1, 2, 10).
playcal calibrate (works today)Bots can play every level on every build, but you want to know how people will do. calibrate takes the bot runs plus a small human panel that played some of the levels, learns how bot pass rates map to human ones, and predicts the human rate for every level the bots played, each with a 95% interval.
playcal calibrate --human panel.jsonl --bot bots.jsonl
Both files use the same event schema. It fits human logits to bot logits per level with a random-effects regression, so levels that the bots get wrong in their own way make every interval wider instead of quietly pulling the line. You need humans on at least 3 levels (5+ attempts each, --min-attempts). From 4 levels on it also leaves each one out in turn and checks whether its real rate lands in the predicted interval; that line tells you how far to trust the rest. With a handful of levels the intervals are wide, and that's the honest answer.
Give it the difficulty you designed for and it becomes a gate. --targets targets.json holds a pass-rate band per level, like {"4": [40, 60]}. Any level whose predicted rate falls outside its band prints level 4: predicted 25%, target 40%-60% and the command exits 1, so CI can stop a build that made a level too hard. playcal report --targets does the same with the measured attempt pass rate.
playcal logs (works today)Boils a Unity Editor.log (or Player.log, or pasted console text) down to what an agent needs. The same error a thousand times becomes one entry with count: 1000, and the first cause is pulled out on its own, since later errors are usually fallout.
playcal logs --json # this machine's Editor.log
playcal logs Editor.log --since "Reloading assemblies" cat Player.log | playcal logs - adb logcat -d | playcal logs - # Android: only the Unity tag is read
Exit code 1 means it found errors. In CI it reads a batch-mode build log the same way, so the job fails on the first cause instead of a wall of fallout:
- run: unity -batchmode -quit -projectPath . -executeMethod Build.Run -logFile build.log || true
playcal loop (works on a live Editor)loop settle waits until the Editor is really ready: two "ready" polls in a row, because a domain reload can flicker. While Unity compiles or reloads, unity status shows no Editor at all, so settle asks unity pipeline list why: Safe Mode, Unity running but stuck on a dialog (editor_blocked), or really no Editor. Two open Editors are reported too, instead of timing out on all of them.
loop run checks the Editor is ready, runs one unity command, checks again, and can check its own work. Each check is one editor status call, which says outright whether the Editor is compiling or reloading; settle's polls are the fallback for a busy or silent Editor and for a write that starts a reload:
playcal loop run "gameobject create" --verify "scene get_hierarchy" --expect "result.roots.*.name=Probe" --diff --json -- --name Probe
--verify runs a read command after the write, --expect asserts on its JSON (path=value, path!=value, path~text, or a bare path for "exists"; * matches any item), and --diff shows what changed between the read before and after. The digest says fault: "infra" when the Editor or CLI broke and fault: "task" when the command itself was wrong, so an agent knows whether to retry or rethink. A write that reported success but didn't land fails with verify_failed (exit 5).
Two traps we hit on a live Editor (Unity 6000.3, Pipeline 0.10.0-exp.1):
--compile also runs unity recompile and fails with compile_error (exit 6) and the errors as file, line, code, message.package resolve says requiresRecompile). loop sees that and waits for the reload to start before it trusts "ready" again; --reload-wait SECONDS forces the same wait for anything else, like a script written to disk.Read, write and --expect passed against that Editor. The Safe Mode branch itself hasn't been seen live yet.
playcal query (works today)A full hierarchy dump can be tens of thousands of tokens when the agent needs three names. query keeps only what you ask for and says how much it cut:
playcal query --unity "scene get_hierarchy" --from "result.roots.**" --where "name~Enemy" --select name --select activeSelf --json
playcal query scene.json --from data.objects --where "tag=Enemy" --select name
--where uses the same syntax as loop --expect. * is any item of a list, ** is anything at any depth.
playcal checkpoint (works today)Saves the project's files before an agent step and brings any save back. Saves are git commits on a private ref (refs/playcal/checkpoints), so your branch, HEAD and staging area don't move and nothing is pushed. .gitignore is respected.
playcal checkpoint save "before level 4 tweak"
playcal checkpoint list playcal checkpoint diff latest playcal checkpoint restore ~1 # one save back; prints how to undo the
只显示了开头部分;其余内容请在仓库中阅读