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MCP verified Apache-2.0 Self-run

Manim Mcp

mcp-wstcpyt-manim-mcp · by wstcpyt

manim mcp server for math animation

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Install

$ agentstack add mcp-wstcpyt-manim-mcp

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access Used
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Passed review? Show it. Paste this badge into your README, it links to the public security report.

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Reliability & compatibility

Security review passed
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stale · 1y ago

Declared compatibility

Claude CodeClaude DesktopCursorWindsurf

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

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About

Manim MCP

A Docker-based environment for creating mathematical animations with Manim, featuring both a CLI interface and a web API with Model Context Protocol (MCP) support for AI assistants.

📑 Overview

This project provides:

  1. Containerized Manim Environment: Run Manim in an isolated, reproducible Docker environment
  2. Web API: Create and manage Manim animations via HTTP requests
  3. MCP Integration: Direct interaction with AI assistants like Claude
  4. File Management: Upload scripts and download generated animations

🚀 Quick Start

Prerequisites

  • Docker and Docker Compose installed on your system

Installation

Option 1: Use the Prebuilt Image (Recommended)

Simply pull the prebuilt image from Docker Hub:

docker pull wstcpyt/manim-docker-mcp:latest

Then run it with docker-compose:

docker compose up -d
Option 2: Build Locally
  1. Clone the repository:

``bash git clone https://github.com/YOUR_USERNAME/manim-docker-mcp.git cd manim-docker-mcp ``

  1. Build the Docker images:

``bash docker compose build ``

Usage

CLI Mode

Create a Python file in the animations directory (see example below), then run:

docker compose run manim -pql animations/example.py ExampleScene
API Mode

Start the API server:

docker compose up -d manim-api

Access the API documentation at http://localhost:8000/docs

🎬 Creating Animations

Basic Example

Create a file animations/example.py:

from manim import *

class CircleToSquare(Scene):
    def construct(self):
        circle = Circle()
        circle.set_fill(BLUE, opacity=0.5)

        square = Square()
        square.set_fill(RED, opacity=0.5)

        self.play(Create(circle))
        self.wait()
        self.play(Transform(circle, square))
        self.wait()

Running the Animation

# CLI mode with preview (-p), low quality (-ql)
docker compose run manim -pql animations/example.py CircleToSquare

# API mode
curl -X POST "http://localhost:8000/run-manim?filepath=/manim/temp/circle_example.py&scene_name=CircleToSquare&quality=low_quality"

📂 Project Structure

manim-docker-mcp/
├── animations/           # Manim animation scripts
├── app/                  # FastAPI application
├── media/                # Generated animations (CLI mode)
├── output/               # Generated animations (API mode)
├── temp/                 # Temporary files
├── uploads/              # Uploaded animation scripts
├── Dockerfile            # Docker image definition
├── docker-compose.yml    # Docker Compose configuration
└── README.md             # This file

🔧 Configuration

Quality Settings

| Flag | Resolution | Frame Rate | Best For | |------|------------|------------|----------| | -ql | 480p | 15fps | Quick previews | | -qm | 720p | 30fps | General use | | -qh | 1080p | 60fps | Presentations | | -qk | 1440p | 60fps | Production videos |

Other Useful Flags

  • -p: Preview the output file
  • -t: Transparent background
  • --save_last_frame: Render only the last frame
  • -c COLOR: Set background color

🌐 API Documentation

Core Endpoints

List Files
GET /list-files?directory=/manim
Write File
POST /write-file?filepath=/manim/temp/example.py
Run Animation
POST /run-manim?filepath=/manim/temp/example.py&scene_name=CircleToSquare
Download Animation
GET /download-file?filepath=/media/videos/example/480p15/CircleToSquare.mp4

Full API documentation is available at the /docs endpoint.

🤖 AI Assistant Integration (MCP)

This project supports the Model Context Protocol (MCP), enabling AI assistants to:

  1. Create Manim scripts based on natural language descriptions
  2. Run animations and provide download links
  3. Browse and manage generated media files

Example MCP session:

User: Create an animation showing a circle morphing into a square
AI: I'll create that for you...

🔍 Advanced Usage

Custom LaTeX

The container includes a minimal LaTeX installation. Custom LaTeX can be used in animations:

formula = MathTex(r"\int_{a}^{b} f(x) \, dx = F(b) - F(a)")
self.play(Write(formula))

Mounting Custom Directories

Modify the docker-compose.yml file to mount additional directories:

volumes:
  - ./my_custom_dir:/manim/custom

🛠️ Troubleshooting

Common Issues

  • Docker not running: Make sure Docker daemon is running
  • Permission errors: The container needs write access to mounted volumes
  • Missing media: Check the correct output directory (media/ for CLI, output/ for API)

Getting Help

If you encounter issues:

  1. Check the Manim documentation
  2. Search existing GitHub issues
  3. Create a new issue with details about your problem

📜 License

This project is licensed under the Apache License 2.0 - see the [LICENSE](LICENSE) file for details.

🙏 Acknowledgements

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.