math-to-manim

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Math To Manim

Ask a question. Get a visual explainer.

Claude Fable 5 GPT 5.6 Sol MCP server Python 3.10 Manim CE License MIT

Featured explainers · What you can ask · How the reasoning works · MCP setup · Native pipelines · Technical reference


Math To Manim turns a math or physics question into a carefully reasoned visual explanation. It finds what the learner needs to know, teaches those ideas in order, checks the mathematics, and builds the explanation in Manim.


Featured Visual Explainers

Erdős Problem 1038 appears as an archival three dimensional landscape with a certified valley and endpoint roots

ERDŐS 1038: THE POTENTIAL LANDSCAPE

A polynomial is usually introduced as a line of symbols, but it can also be seen as a landscape made by its roots. Imagine every root pressing into a flexible sheet stretched above the number line. Taken together, the roots raise and lower that sheet. The transparent plane in the explainer marks zero. Wherever the landscape falls beneath it, the polynomial has size less than one. The footprint under the plane is therefore the exact set whose width the problem asks us to measure.

That turns the question into something physical. How should the roots be arranged to make the submerged footprint as narrow as possible, or as wide as possible? For the narrow side, clusters of roots can be gathered toward their centres without making the footprint larger. Repeating that idea leads toward an increasingly fine, one sided distribution of roots. No finite polynomial quite reaches the limiting shape, but a sequence of them gets arbitrarily close. Its width is 1.834430475762661…. This is the certified floor shown by the curved valley.

The widest case is beautifully simpler. Put the roots at the two endpoints, −1 and +1, in equal numbers. This produces the family f(x) = (x² − 1)ᵐ, and the region where the polynomial is smaller than one runs from −√2 to +√2. Its width is therefore 2√2. The explainer ends by contrasting two different kinds of extreme: a lower value that can be approached forever but never attained by a finite polynomial, and an upper value reached exactly by piling the roots at the endpoints.

Watch the complete 79 second visual explainer · Read the complete Sol production prompt


A deformed coordinate lattice reveals local volume change before the camera pulls back to the global map

THE JACOBIAN CONJECTURE. This explainer separates local certainty from global truth. A small cube becomes a parallelepiped, making the Jacobian determinant visible as local volume change. The camera then pulls back to show why a map can be reversible nearby without being reversible everywhere.


Explore every visual explainer in the motion showcase

What Is Math To Manim

Math To Manim turns a math or physics question into a carefully reasoned visual explanation. It works backward to identify what the learner needs to know, rebuilds those ideas in teaching order, checks the mathematics, and animates the explanation in Manim.

Manim is the open source animation engine originally created by Grant Sanderson for 3Blue1Brown. It powers many of the most recognizable math and physics animations online. This project uses the edition maintained by the Manim community.

The reasoning process is the product. Math To Manim does not jump directly from a sentence to Python. It first decides what must be understood, what must be shown, and in what order each idea should appear.

What Can I Ask

Middle School Arithmetic

Explain why a negative number times a negative number becomes positive to an eighth grade student. Use a number line, one everyday analogy, and one worked example.

Geometry

Show why the Pythagorean theorem works without assuming advanced algebra. Build the squares on all three sides and rearrange their areas.

Introductory Algebra

Teach slope using three ramps. Explain rise over run, compare steepness, then solve one line equation.

High School Physics

Explain conservation of momentum using two carts that collide. Show the momentum arrows before and after impact.

University Mathematics

Explain Fourier series as rotating vectors that rebuild a signal. Begin with a circle and add one frequency at a time.

Research Mathematics

Show why one loop around an exceptional point swaps the eigenvalue branches. Assume I know complex numbers but not covering spaces.

A Useful Prompt Recipe

Explain [topic] to [learner]. Assume they already know [starting point]. Use [visual metaphor or physical model]. Work through [specific example]. End with [summary or check question].

You can name the learner's age, prior knowledge, pace, preferred visual model, worked example, notation level, and final comprehension check. A simple homework question is enough. The pipeline expands it into a teaching plan.

How The Reasoning Pipeline Works

  1. Understand the learner. Identify the real question, the audience, and the intended depth.
  2. Find the missing prerequisites. Work backward until every branch reaches ideas the learner already knows.
  3. Build the teaching sequence. Walk those ideas forward in the order that makes the final concept feel earned.
  4. Choose the mathematics. Select the definitions, equations, examples, and checks that carry the explanation.
  5. Plan the visuals. Decide what appears on screen, what changes, and where the camera guides attention.
  6. Compose the Manim scene. Turn the teaching plan into complete, addressable visual objects and timing.
  7. Validate the result. Check code structure, mathematical presentation, readability, and camera rules.
  8. Render, inspect, and repair. Produce the explainer, review the evidence, and correct visible defects.

Make Your First Explainer

The easiest path is a conversation with an assistant that can use MCP.

pip install -e ".[mcp]"
math-to-manim serve-mcp

Add the server to your MCP client:

{
  "mcpServers": {
    "math-to-manim": {
      "command": "math-to-manim",
      "args": ["serve-mcp"]
    }
  }
}

Once the server is connected, type this in your assistant:

Use Math To Manim to create a visual explainer for my eighth grade student. Explain why solving an equation means doing the same thing to both sides. Use a balance scale, solve 3x + 5 = 20, and end with one practice question.

You do not need to memorize tool names. The assistant starts the explainer. The assistant reports progress. The assistant can inspect every reasoning artifact. The final scene and render remain in the local run directory.

Choose A Native Pipeline

Math To Manim contains two complete and independent ways to create a visual explainer. Choose the command line account you already use. Neither pipeline routes through the other.

Mythos

Mythos uses the Claude CLI and a six agent charter chain. It reasons through learner intent, prerequisite mapping, curriculum, mathematics, camera direction, and scene composition.

math-to-manim doctor --ping
math-to-manim run "Explain fractions with a folding paper model for a sixth grade learner." --render -q m

Sol

Sol uses the logged in Codex CLI and durable specialist stages. Each role saves its artifact and session so the run can be inspected, resumed, and repaired by the responsible specialist.

math-to-manim-sol doctor
math-to-manim-sol run "Explain fractions with a folding paper model for a sixth grade learner."

Read the complete Sol contract.

Kimi

Kimi uses an agent architecture that is different enough to warrant its own repository. Explore Kimi K3 Manim.

Installation

git clone https://github.com/HarleyCoops/Math-To-Manim.git
cd Math-To-Manim
python -m venv .venv
pip install -e ".[dev,render,mcp,api]"
python -m pytest -q

Use math-to-manim doctor --ping for Mythos. Use math-to-manim-sol doctor for Sol. Run the appropriate check before a live request so login and rendering problems appear immediately.

Run Artifacts

Every run keeps its reasoning, scene source, validation evidence, and manifest inside the repository. Mythos writes to runs/mythos/. Sol writes to runs/sol/. Open the intermediate JSON when you want to understand or revise how the explainer was built.

The artifacts tell a readable story:

learner intent
      ↓
prerequisite map
      ↓
teaching sequence
      ↓
mathematics and examples
      ↓
visual plan
      ↓
Manim scene
      ↓
validation, render, and repair evidence

MCP Reference

These tools are available to assistants and integrations. A learner can simply ask for an explainer in ordinary language.

Tool Purpose
m2m_create_animation Starts the Mythos reasoning chain as a background job
m2m_get_job Reports live progress for each reasoning stage
m2m_list_runs Lists local runs with the newest first
m2m_get_run Returns the manifest and artifact list for one run
m2m_get_artifact Reads a reasoning artifact such as the prerequisite map
m2m_get_scene_code Returns the generated Manim scene
m2m_cinematic_charter Returns the visual composition contract

For a headless client, use the reference driver:

python scripts/drive_mcp_pipeline.py "why does a spinning handle flip itself?" --render -q l --log runs/drive.log

REST API

The REST API exposes Mythos for applications and background jobs.

pip install -e ".[api]"
math-to-manim serve-api

OpenAPI documentation is available at http://127.0.0.1:8642/docs.

Method Route Purpose
GET /health Reports service health and version
POST /v1/runs Submits a prompt and returns a job record
GET /v1/jobs/{job_id} Reports queued, running, completed, or failed state
GET /v1/runs Lists the local run ledger
GET /v1/runs/{run_id} Returns a manifest and artifact listing
GET /v1/runs/{run_id}/artifacts/{name} Returns one JSON or Python artifact 
curl -s -X POST localhost:8642/v1/runs \
  -H "Content-Type: application/json" \
  -d '{"prompt": "explain Fourier epicycles as rotating vectors", "render": false}'

Configuration

Mythos reads configuration from the environment or a local .env file.

Variable Default Purpose
M2M_MODEL claude-fable-5 Selects the baseline model
M2M_MODEL_FALLBACKS claude-opus-4-8,claude-sonnet-5 Lists models used when the baseline has a model failure
M2M_COMMAND claude Selects the explicit backend command
M2M_TIMEOUT 900 Sets the model call budget in seconds
M2M_RENDER_TIMEOUT 1800 Sets the render budget in seconds
M2M_RUNS_DIR runs/ Selects the local run directory
M2M_MANIM automatic Overrides the Manim executable

Read the Sol contract for its Codex CLI login, staged sessions, resume command, manifest, and environment.

Testing

python -m pytest -q
math-to-manim run "the heat equation" --offline
math-to-manim-sol run "the heat equation" --offline

Offline runs validate the complete artifact shape without model calls or an expensive render.

More From The Project

The motion showcase preserves every visual study and older animation. The Prime Intellect notes describe reinforcement learning work for visual repair. The roadmap tracks future work. The agent guide defines repository boundaries and verification rules.

Repository Layout

mythos/            Claude CLI reasoning chain, service, API, MCP, and CLI
sol/               Codex CLI specialist pipeline
examples/mythos/   Hand finished Mythos examples
docs/showcase/     Complete visual archive
tests/             Offline repository tests
runs/              Local reasoning and render artifacts
archive/           Retired implementations kept for history
legacy/            Original January 2025 repository material

License

MIT.

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