manim-mcp-rag
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@manim-mcp-ragcreate an animation of a rotating square"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
ο»Ώ# Manim MCP β DeepSeek Only
Altin Kural: Sadece DeepSeek. Baska hicbir LLM provider YOK. OpenAI SDK β DeepSeek endpoint. Google Gemini, OpenAI, Claude import edilmez.
Manim ile matematik animasyonlari ureten MCP sunucusu. DeepSeek LLM + ChromaDB tabanli RAG ile ilgili Manim kod orneklerini getirip, kullanici istedigi animasyonu uretir ve render eder.
Ozellikler
π¬ Manim Community animasyon uretimi (DeepSeek
deepseek-chat/deepseek-reasoner)π§ ChromaDB tabanli RAG β vektor arama ile ilgili kod orneklerini getirir
π Coklu kaynak indexleme β 3Blue1Brown videolari, animg kutuphanesi, Manim Kindergarten verisi, Pisagor ve ozel sahneler
π Storyboard katmani β sahne planini JSON olarak uretir (
storyboard.json)π Geri besleme dongusu β basarili render'lar RAG'e geri beslenir (
feed_rag.py)π₯οΈ CLI + MCP β hem terminal hem VS Code MCP uzerinden kullanilabilir
Related MCP server: Manim MCP Server
Hizli Baslangic
# 1. Kur
pip install -r requirements.txt
# 2. .env dosyasini duzenle (DEEPSEEK_API_KEY zorunlu)
# .env.example dosyasini .env olarak kopyala, API keyini yaz
# 3. (Istege bagli) RAG indexlerini olustur
python index_animg.py
python index_3b1b_videos.py
python index_pisagor.py
# 4. Sunucuyu baslat (1. terminal)
python server.py
# 5. CLI'yi baslat (2. terminal)
python cli.py
# 6. Test et
>>> Bir daire ciz ve kaydir
>>> /doc How to animate a square transforming into a circle
>>> /healthMimarisi
βββ index_*.py βββΆ ChromaDB (chroma_data/)
β
storyboard.json βββ generate_storyboard.py
β
cli.py ββHTTPβββΆ server.py ββOpenAI SDKβββΆ api.deepseek.com
β β
βββ manim_mcp (manim-mcp-original)
β βββ core/rag.py (ChromaDBService - RAG)
β βββ core/tracker.py (RenderTracker)
β βββ prompts/ (system prompt sablonlari)
β βββ config.py (ManimMCPConfig)
β
render_with_rag.py βββ RAG retrieval (5 koleksiyon: patterns, components, helpers, scenes, 3b1b)
β
βββ feed_rag.py βββΆ basarili render'lar RAG'e geri beslenirDosyalar
Dosya | Gorevi |
| Flask MCP sunucusu (JSON-RPC) |
| Terminal arayuzu |
| OpenAI SDK ile DeepSeek API |
| MCP tool tanimlari (DeepSeek/OpenAI format) |
| .env tabanli yapilandirma (DeepSeek + MCP + Manim + RAG) |
| RAG destekli animasyon uretim pipeline'i |
| Storyboard JSON uretici (ornek: Pisagor) |
| Basarili render'lari ChromaDB'ye besler |
| animg kutuphanesi β ChromaDB |
| 3Blue1Brown videolari β ChromaDB |
| Pisagor ozel verisi β ChromaDB |
| Manim Kindergarten verisi β ChromaDB |
| Ozel sahneler β ChromaDB |
| Cekirdek paket (RAG, tracker, promptlar) |
| Ornek storyboard tanimi |
| VS Code MCP yapilandirmasi |
| Sablon .env dosyasi |
RAG (ChromaDB)
Embedding ve vektor arama ChromaDB uzerinden yapilir (TF-IDF degil)
Veri yolu:
MANIM_MCP_CHROMADB_PATH(varsayilan:./chroma_data)render_with_rag.py5 koleksiyondan paralel ceker:patterns,components,helpers,scenes,3b1bRAG protokolu icin:
RAG_PROTOCOL.md
Testler
python test_code_generation.py # kod uretim testi
python test_critical.py # kritik akis testleri
python test_precision.py # hassasiyet testleri
python test_production.py # uretim testleriNeden DeepSeek?
Orijinal paulnegz/manim-mcp reposu google.generativeai kullanir. Bu su demek:
Kod Gemini SDK import eder ama
DEEPSEEK_API_KEYayarlanmistirGoogle SDK
GOOGLE_API_KEYarar, DeepSeek keyini yok sayarYa crash olur ya da sessizce Geminiye gider
Bizim cozumumuz: from openai import OpenAI + base_url="https://api.deepseek.com"
DeepSeek, OpenAI API uyumlu oldugu icin baska hicbir SDKya gerek yok.
MCP Olarak Kullan
mcp.template.json dosyasini VS Code MCP ayarlarina kopyala, DEEPSEEK_API_KEYi yaz.
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