claude-quickstarts vs LlamaIndex
Which should you use? A side-by-side look at what each one does, who it suits, what it costs, how hard it is to set up, and where each falls short.
Open source · MIT
Starter projects that show how to build apps with the Claude API, from support agents to browser and desktop a
Open source · MIT
Python framework for building LLM apps that query your own documents and data.
The short answer
Choose claude-quickstarts if you need…
- Developers who want to see working Claude API examples before writing their own app
- Teams evaluating which Claude capabilities fit a use case such as support, data analysis, or browser automation
- Developers already using Slack, Linear, or Sentry who want an example integration to study
- Students learning how AI agents are wired together with tools and sessions
Choose LlamaIndex if you need…
- Python developers building retrieval-augmented generation (RAG) apps over private documents
- Teams wanting a modular toolkit where they can swap LLM, embedding and vector store providers
- Developers building agent workflows that query their own data
- Beginners who want a short path to a working document question-answering prototype
Side-by-side
| claude-quickstarts | LlamaIndex | |
|---|---|---|
| Type | Learning resource | Library |
| Price | Free and open source | Free and open source |
| Licence | MIT | MIT |
| GitHub stars | 19.1k | 52.8k |
| Setup difficulty | Intermediate | Intermediate |
| How you get it | Clone and build from source | Install with a package manager |
| Main language | TypeScript | Python |
| Last code update | 6 days ago | 10 days ago |
What each one is
claude-quickstarts
Claude Quickstarts is a collection of example projects from Anthropic meant to help developers begin building applications on the Claude API. Each project is a starting point you can run, read, and then adapt to your own needs. The collection covers a range of examples, including a customer support agent, a financial data analyst, computer and browser use demos, and several Managed Agents integrations with tools like Slack, Linear, and Sentry.
LlamaIndex
LlamaIndex is an open-source Python framework for connecting large language models to your own data, such as PDFs, documents, APIs and SQL databases. It provides connectors to load data, ways to structure it into indexes, and retrieval tools that feed relevant context to an LLM. The README also notes that the company's main focus has shifted toward its commercial LlamaParse document platform, with the open-source framework still available.
Best for
claude-quickstarts
- Developers who want to see working Claude API examples before writing their own app
- Teams evaluating which Claude capabilities fit a use case such as support, data analysis, or browser automation
- Developers already using Slack, Linear, or Sentry who want an example integration to study
- Students learning how AI agents are wired together with tools and sessions
LlamaIndex
- Python developers building retrieval-augmented generation (RAG) apps over private documents
- Teams wanting a modular toolkit where they can swap LLM, embedding and vector store providers
- Developers building agent workflows that query their own data
- Beginners who want a short path to a working document question-answering prototype
Strengths
claude-quickstarts
- Maintained by Anthropic and published under the MIT license, so the code can be reused and modified
- Covers many different use cases, from chat apps to scheduled agents and browser or desktop control
- Each quickstart is in its own folder, so you can work on one example without setting up the others
LlamaIndex
- Large ecosystem of over 300 integration packages, per the README
- Modular design lets you customize or replace components like retrievers and query engines
- Offers both a high-level API for quick starts and lower-level APIs for advanced control
Not ideal for
claude-quickstarts
- Non-developers who want a ready-made app without writing or configuring code, since the README assumes API setup
- Anyone needing production-ready code, because several projects say they are reference or teaching examples rather than production code
- Users without a Claude API key, since the README says one is needed to use these quickstarts
LlamaIndex
- Non-programmers, since it is a Python library that requires writing code
- Projects that need a fully managed hosted service, because the README points to LlamaParse for the hosted offering and the framework is a toolkit you run yourself
- Users who only need simple one-off document parsing, where a standalone parser may be simpler
Trade-offs
claude-quickstarts
- Projects vary a lot in complexity and maturity; some are explicitly minimal examples and not production code
- The README is truncated and does not give full setup steps for each project, so you will need to read each subfolder's instructions
- Several projects depend on specific Claude features, such as Managed Agents or newer toolset versions, which may change over time
LlamaIndex
- The README says the company's primary focus has shifted to LlamaParse, so the open-source framework is secondary to its commercial product
- The README is not updated as often as the documentation, so you should check the docs for current details
- Many separate integration packages means you must choose and install the ones you need
Getting started
claude-quickstarts
Clone the repository
git clone https://github.com/anthropics/claude-quickstartsLlamaIndex
Install core and selected integrations
pip install llama-index-coreAdd an LLM integration
pip install llama-index-llms-openaiFrequently asked questions
What is the difference between claude-quickstarts and LlamaIndex?
claude-quickstarts: Starter projects that show how to build apps with the Claude API, from support agents to browser and desktop a. LlamaIndex: Python framework for building LLM apps that query your own documents and data. claude-quickstarts suits developers who want to see working claude api examples before writing their own app, while LlamaIndex suits python developers building retrieval-augmented generation (rag) apps over private documents.
Are claude-quickstarts and LlamaIndex free?
claude-quickstarts: Free and open source. LlamaIndex: Free and open source.
Is claude-quickstarts or LlamaIndex more popular?
LlamaIndex has more GitHub stars (52.8k) than claude-quickstarts (19.1k). Popularity isn't the same as fit — check which one matches your use case above.
What are other alternatives to claude-quickstarts and LlamaIndex?
Other options people compare them with include LangChain, OpenAI Cookbook, LangGraph, PageIndex, OpenAI Agents SDK.
Keep comparing
Built from our catalogue entries for both products: open-source details come from each project's README (AI-assisted, refreshed weekly) and GitHub data; AI-tool details are editorial. Spotted something wrong? Let us know from either product's page.