# Manim

> Use this tool when you need to create mathematical animations from natural language descriptions, solving the problem of tedious video production and code writing for educational or explanatory content. It takes in text inputs and outputs rendered video animations, leveraging a knowledge base and multiple LLM agents to generate high-quality results. Ideal for use in educational settings, explainer videos, or technical demonstrations where dynamic visualizations are required.

Canonical page: https://skillsregistry.net/skills/paulnegz-manim  
JSON: https://api.skillsregistry.net/v1/skills/paulnegz-manim

## Description

Manim MCP server converts natural language descriptions into rendered mathematical animations using the Manim library. It orchestrates multiple LLM agents to analyze concepts, plan scenes, generate and validate Manim code, render videos with secure sandboxing, and track results in S3 with SQLite. Supports multiple LLM providers and includes a 5,300+ document knowledge base for high-quality code suggestions.

## Trust

- **Trust score (0–1):** 0.00
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/paulnegz-manim)
- **Repository:** <https://github.com/paulnegz/manim-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "paulnegz-manim"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/paulnegz-manim` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/paulnegz-manim/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt