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Chalkcast

作者:FredMichel版本 0.1.0i★ –i在你的电脑上运行
注册名称io.github.FredMichel/chalkcast

安装

概览

作者提供的说明(英文原文)

Author, render and visually verify Manim math animations from natural language

PopNx MCP 的三大支柱

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。

它能帮你做什么

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。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 其他

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 注册中心没有列出需要填写的密钥。

你需要

  • PyPI已安装 Python 的 uv(用于 uvx 命令)

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": {
    "chalkcast": {
      "command": "uvx",
      "args": [
        "chalkcast"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add chalkcast -- uvx chalkcast

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "chalkcast": {
      "command": "uvx",
      "args": [
        "chalkcast"
      ]
    }
  }
}

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。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "chalkcast": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "chalkcast"
      ]
    }
  }
}

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。

它能做什么

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。

基础检查i

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

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 FredMichel 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    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“其他”中的其他服务器比较i

  • 星标数多于此分类中其他 32686 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 32686 个服务器的 74% 更新
  • 基础检查结果等于或优于此分类中其他 32686 个服务器的 100%

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。

常见问题

Chalkcast 安全吗?

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。

它需要哪些密钥或代码?

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。

它在我的电脑上运行还是在云端?

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)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.1.0)于12天前进入注册中心。

哪些应用可以使用它?

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)。

有什么可以替代它?

同一分类中有:Spec Driven Development, Remote Desktop Commander, Microsoft Exchange Online MCP

替代选择

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

Spec Driven Development

作者:formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

在你的电脑上运行★ 440MIT14个月前更新
安装

Remote Desktop Commander

作者:desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

在云端运行★ 211前天更新
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Exchange Online admin for MSPs: forwarding audits, EWS posture and offboarding, no PowerShell

在你的电脑上运行今天更新
安装

作者的 README

打开 README

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。

Chalkcast

Describe a concept. Get a *verified* animated explainer.

Chalkcast is an MCP server that lets an agent author, render, and visually verify Manim animations — so the output is a video that's actually correct on screen, not a plausible script that renders wrong.

One continuous animation, authored, verified and rendered entirely through the MCP server (passed on the first render): a Fourier series grows harmonic by harmonic into a square wave, and the Gibbs overshoot (the true one, ≈ 1.179) stays at the edges. Reproduce it with python examples/showcase.py .


Who it's for

  • Educators & students — turn "explain the Fourier series" into a clean animated explainer, without learning Manim or writing LaTeX by hand.
  • STEM content creators — produce 3Blue1Brown-style animations in minutes instead of hours of coding and debugging renders.
  • Agents & tooling — a typed, verifiable MCP surface an AI can drive end to end, with a verdict it can act on instead of a video it can't inspect.

Why another Manim MCP?

Existing Manim MCP servers give the agent one tool: *run this code, return the video.* The agent writes Manim blind and hopes — but Manim is unforgiving (a LaTeX typo, an off-screen label, two terms overlapping, a transition firing before its target exists). The video "renders" and is still wrong, and the agent has no way to know.

Chalkcast gives the agent eyes and a correction loop:

author scene ──► render ──► inspect (verification lanes) ──► verdict

▲ │ └──────────────── fix obligations ◄──── needs_fix ─────────┘

Every render returns evidence (the artifact + sampled frames) and a structured verdict. Problems become obligations that block export until resolved. See docs/SPEC.md for the full design.

Install

One command (Claude Code; needs uv):

claude mcp add chalkcast -- uvx --python 3.12 --from "chalkcast[render]" chalkcast serve

--python 3.12 matters: Chalkcast needs Python ≥ 3.11, and uv downloads one if the system Python is older (macOS ships 3.9). Then just ask in natural language.

Or with pip, into any Python ≥ 3.11 environment:

pip install "chalkcast[render]"

claude mcp add chalkcast -- chalkcast serve

[render] brings Manim and a bundled ffmpeg. Equations also need a LaTeX distribution. chalkcast doctor checks everything and prints the exact fix command for your OS:

chalkcast doctor               # Manim / LaTeX / dvisvgm / physics.sty / ffmpeg

chalkcast demo # builds + verifies + renders the demo scene

macOS: pycairo (pulled in by Manim) has no macOS wheel and builds from

source, so it needs brew install cairo pkg-config first. On a machine where

Manim's native deps were built by hand, see scripts/dev-env.sh and

scripts/serve.sh.

What the agent gets

GroupTools
Sessionopen_project · inspect_project · close_project
Authoringadd_scene · add_equation · add_plot · add_area · add_riemann · add_text · add_shape · add_parameter · add_step
Editingupdate_object · remove_object (cascade) · remove_step
Verificationinspect_render (measured, no video) · fix_scene (auto-repair)
Renderingrender_scene · render_frame
Exportexport_gif (blocked while error obligations remain)
Discoveryinspect_environment
  • Continuous animation: add_parameter("t"), use t in plot expressions or shape anchors (at_x="t"), then add_step("tween", param="t", value=6.28). Curves, areas and anchored dots follow it frame by frame. with_previous=True plays a step at the same time as the one before.
  • Fail fast, nothing implicit: expressions are validated when authored (an AST whitelist: x, math functions, np. , declared parameters). Colors, ranges, step targets, timeline order, and arguments that don't apply to a shape or step are rejected with a message saying what to do. Edits are all-or-nothing. Side effects (cascade removals, regrouped steps, redeclared parameters, default ranges) are reported in the result. export_gif refuses a render that predates the latest edit. Thirty-two independent audits (22, then 17, 14, 8, 4, 9, 4, 7, 5, 5, 7, 8, 5, 8, 7, 7, 10, 4, 5, 5, 8, 7, 7, 5, 7, 9, 7, 4, 10, 9, 7 and 6 findings, the last with no high-severity one; in the last thirteen, 9, 10, 8, 10, 9, 9, 9, 9, 9, 10, 8, 9 and 10 of 10 fresh explainers reached a correct GIF within two renders, and in the last one every verdict matched its frames; the last twenty-three built realistic explainers end to end and compared verdicts with frames, one of them over the real MCP stdio protocol) are pinned one test per finding in tests/test_ergonomics.py.
  • Faithful plots: dense sampling, curves split at jumps and poles (no invented risers or overshoot), clipping to the axes. A *fidelity* lane measures the drawn curve against the true function. Areas and Riemann sums are refused when they could not show the integral (function undefined or off the axes, y = 0 not visible).
How verification works

inspect_render builds the real Manim objects without encoding video (1–3 s) and measures them: exact bounding boxes, curve and axis ink, the drawn-vs-true error of every graph, and a strict LaTeX compile (Manim's batch mode silently "recovers" from LaTeX errors). Lanes: framing · collision · legibility · timing · compile · fidelity · range. fix_scene repairs the mechanical problems (moves, rescales, resampling) and leaves the rest as obligations for the agent.

Measured on labelled scenes (chalkcast bench, chalkcast bench --holdout N). Each held-out set was written and labelled (and checked frame by frame) by an author who never read the verifier. The first run of each set is the honest out-of-sample figure:

SetCasesFirst run: detection / false positivesBugs that run exposed
Held-out 139 (24 defective)95.8 % / 7.7 %over-strict safe margin; aliasing taken for a jump
Held-out 247 (31 defective)90.3 % / 12.8 %estimated noise after a compile error; straight arrows and box sides sampled only at their ends; equation size judged by box height
Held-out 344 (26 defective)96.2 % / 0 %an arrow's shaft was never sampled (only its tip)
Held-out 446 (25 defective)96.0 % / 0 %a label written *during* a zoom-in was excused as an intentional crop

After each set's bugs were fixed, every set (and the 40-case development set) scores 100 % / 0 %. From then on they are regression tests (tests/test_measured.py), not independent measures. Held-out 3 was written after the fixes for sets 1 and 2, and held-out 4 (continuous tweens, simultaneous beats, transforms, camera moves) after eleven ergonomics audits; each was run once, untouched. Held-out 4 is the current out-of-sample estimate.

Example (what the agent does)

open_project(theme="chalkboard")

add_scene(title="Area under a parabola") add_text("Area under y = x^2", y=3) add_plot(functions=[{"expr":"x**2","color":"YELLOW"}], x_range=[0,2,1], y=-0.8) add_equation(r"\int_0^1 x^2 \, dx = \tfrac{1}{3}", y=2) add_step("write", targets=["text_1"]) add_step("write", targets=["plot_1"]) add_step("write", targets=["equation_1"]) add_step("highlight", targets=["equation_1"]) inspect_render() # -> measured verdict in ~2 s, no video fix_scene() # -> repairs framing / collision / fidelity if needed render_scene() # -> video + frames + verdict + obligations export_gif() # -> shareable GIF (blocked if error obligations remain)

Status

Alpha. Scientific correctness is tested numerically (tests/test_science.py): shaded areas equal their integrals, Riemann rectangles their sum, drawn curves their function (including sin 30x), and the Gibbs peak its theoretical value. On PyPI and the MCP Registry (io.github.FredMichel/chalkcast). Vision-based intent verification is next (see docs/SPEC.md).

License

MIT.

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