A collection of notebooks/recipes showcasing some fun and effective ways of using Claude.
47.3k
Stars
5.6k
Forks
284
Open issues
30
Contributors
AI Analysis
Claude Cookbooks is an official Anthropic collection of Jupyter notebooks and code examples demonstrating practical applications of the Claude API across capabilities like classification, RAG, summarization, and tool integration. It serves developers building AI applications with Claude, from beginners learning API fundamentals to experienced practitioners implementing advanced patterns; it is not suitable for those working exclusively with other LLM providers.
Inferred from signals mentioned in the README (tests, CI, type safety) — not a review of the actual code.
AI's overall editorial judgment — not an average of the bars above, can weigh other factors too.
Anthropic's official Claude API cookbook: practical notebooks for developers building with Claude
Claude Cookbooks is Anthropic's official collection of Jupyter notebooks and code guides covering RAG, tool use, multimodal vision, embeddings, and third-party integrations with the Claude API. It targets developers who are new to or actively building on Claude and need copy-paste-ready starting points. With ~45,700 stars and active maintenance through mid-2026, it functions as a primary onboarding resource for the Claude developer ecosystem rather than a standalone library.
Created in August 2023 shortly after Claude's public API launch, it mirrors the cookbook format popularized by OpenAI's similar repository. It has grown steadily alongside Claude's rising developer adoption.
Star growth tracks Claude's broader market momentum—Claude 3 (Opus/Sonnet/Haiku) launch in early 2024 and subsequent Claude 3.5/3.7 releases drove developer interest. The 82 stars in 7 days (as of June 2026) reflects a mature plateau rather than viral growth, consistent with a reference resource rather than a trending tool.
Adoption not directly verified via deployment metrics, but strong indirect signals exist: official Anthropic ownership, 5,357 forks (high relative to stars, suggesting active copying and adaptation), and positioning as the primary developer reference alongside official docs. Community engagement via Discord and issues is referenced explicitly.
Likely organized as a flat collection of self-contained Jupyter notebooks grouped by capability category (tool use, multimodal, RAG, third-party integrations). Each notebook appears to be independently runnable given only an API key. No framework or installable package is implied—this is documentation-as-code rather than a software library.
Not documented in README. As a notebook collection, automated CI testing is not expected; notebooks are likely validated manually or via spot checks before merging.
Last push was June 9, 2026—12 days before the evaluation date—indicating active, ongoing maintenance. The repository accepts community contributions via issues and PRs, and the README links to current Anthropic developer docs. No signs of abandonment or stagnation.
ADOPT IF: you are building on the Claude API and want vetted, official starting points for common patterns like RAG, tool use, or multimodal workflows—especially if you are onboarding a team. AVOID IF: you need production-grade, installable libraries or abstractions; these are learning notebooks, not deployment-ready components. MONITOR IF: you are evaluating the maturity and breadth of the Claude developer ecosystem over time—the notebook count and update cadence serve as a proxy for Anthropic's developer experience investment.
Independent dimensions
Mainstream potential
5/10
Technical importance
4/10
Adoption evidence
5/10
- Notebooks may lag behind Claude API updates (new model versions, changed parameters) causing silent breakage if not regularly validated against the live API.
- Quality consistency across notebooks may vary if community contributions are accepted without rigorous review standards.
- As a collection of notebooks rather than a library, there is no versioning or pinned dependency management—users must resolve environment issues themselves.
- Dependency on third-party services (Pinecone, Voyage AI, AWS) in some notebooks introduces external points of failure and cost that are outside Anthropic's control.
- Star count and fork count may overstate active use—many forks may be exploratory rather than representing ongoing production integrations.
Likely to continue growing steadily as Claude API adoption expands, with new notebooks tracking new Claude capabilities. Will probably remain the canonical starting point for Claude API developers rather than evolving into a reusable library.
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Languages
Information
- Language
- Jupyter Notebook
- License
- MIT
- Last updated
- 7h ago
- Created
- 35mo ago
- Analyzed with
- anthropic/claude-haiku-4-5
Stars over time
Contributors over time
Top 100 contributors only — repos with more will plateau at 100.
Top contributors
Recent releases
No releases published yet.
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Also official Anthropic content but appears narrower in scope—likely entry-level getting-started examples. Cookbooks is broader and more task-specific, making them complementary rather than competing.
A community-maintained collection with more stars, suggesting significant organic interest. Likely less curated and not officially endorsed, making it a supplementary rather than authoritative reference.
Higher star count focused on Claude Code specifically—a narrower, faster-growing niche. Targets power users and agentic workflows rather than API beginners.
The clear conceptual predecessor and benchmark. OpenAI's version benefits from longer history and larger installed base. Claude Cookbooks follows the same structural pattern but is younger and Claude-specific.
Far higher star count because it is an actual product (CLI tool), not a documentation collection. Not directly comparable—different category entirely.