#4646th of 110 in Learning and cookbooks
genai-showcase
MongoDB's notebooks, apps and workshops for building RAG and agents
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- Stars
- 4.3k
- License
- MIT
- Last commit
- Oct 2026
- Language
- Jupyter Notebook
Missed the latest GitHub check; these facts may be older.
Overview
A collection of Jupyter notebooks, JavaScript and Python apps, self-paced workshops and partner contributions showing how to use MongoDB in GenAI projects. Examples cover RAG, AI agents, evaluations and industry-specific use cases, with MongoDB as vector store, operational database and agent memory. Every example needs a MongoDB Atlas cluster connection string.
Who it is for: Developers learning to build RAG and agents on MongoDB Atlas
Strengths
- Covers RAG, agents and evaluations in runnable notebooks
- Includes self-paced workshops alongside notebooks and full sample apps
- MIT licensed, with partner-contributed examples in their own folder
Weaknesses
- Every example requires a MongoDB Atlas cluster and connection string
- Examples are built around MongoDB, so they do not show other vector stores
- No Docker or compose setup; each example is configured separately
- No tagged releases, so examples are not versioned
What it needs
- Needs MongoDB Atlas
Also in Learning and cookbooks
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|---|---|---|
| 1 | ai-engineering-from-scratchHands-on AI engineering curriculum with 542 lessons across 20 phases | 92 out of 100 |
| 2 | generative-ai-for-beginners21-lesson course on building generative AI apps in Python and TypeScript | 83 out of 100 |
| 3 | rag_techniquesCollection of 42 runnable notebooks implementing RAG techniques | 82 out of 100 |
| #4 | cs249r_bookOpen textbook and course materials for machine learning systems engineering | 82 out of 100 |
| #5 | agents-towards-productionJupyter tutorials for taking LLM agents from prototype to production | 82 out of 100 |