head to head · open source
claude-context vs RAGLight
claude-context has 12,667 GitHub stars, 939 forks, 146 open issues and last shipped 4 months ago. RAGLight has 672 stars, 102 forks, 22 open issues and last shipped 20 days ago. claude-context leads on adoption by 1,785% (12,667 vs 672 stars). claude-context is written in TypeScript under MIT; RAGLight is written in Python under MIT. claude-context has attracted 7% as many forks as stars, RAGLight 15%. RAGLight was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 2 topic tags (agentic-rag, mcp), so they are genuine substitutes rather than adjacent tools.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
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Side by side
| claude-context | RAGLight | |
|---|---|---|
| GitHub stars | ★ 13K | ★ 672 |
| License | MIT | MIT |
| Written in | TypeScript | Python |
| Last push | 2026-07-14 | 2026-10-16 |
| Forks | ⑂ 939 | ⑂ 102 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick claude-context if
- You weight community size — 13K stars and counting
- You want the MIT license terms
- Your stack matches TypeScript
- You value the larger contributor base for long-term maintenance
pick RAGLight if
- You want the RAGLight feature set and don't need the biggest community
- You prefer the MIT license terms
- Your stack matches Python
- You evaluated both and RAGLight fits your workflow better
About claude-context
🆕 Looking for persistent memory for Claude Code? Check out memsearch Claude Code plugin — a markdown first memory system that gives your AI agent long term memory across sessions. Your entire codebase as Claude's context Claude Context is an MCP plugin that adds semantic code search to Claude Code and other AI coding agents, giving them deep context from your entire codebase. 🧠 Your Entire Codebase as Context : Claude Context uses semantic search to find all relevant code from millions of lines. No multi round discovery needed. It brings results straight into the Claude's context. 💰 Cost Effective for Large…
read the full claude-context overview →
About RAGLight
RAGLight RAGLight is a lightweight and modular Python library for implementing Retrieval Augmented Generation (RAG) . It enhances the capabilities of Large Language Models (LLMs) by combining document retrieval with natural language inference. Designed for simplicity and flexibility, RAGLight provides modular components to easily integrate various LLMs, embeddings, and vector stores, making it an ideal tool for building context aware AI solutions. 📚 Table of Contents Requirements Features Import library Chat with Your Documents Instantly With CLI Ignore Folders Feature Ignore Folders in Configuration Classes…
read the full RAGLight overview →
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Frequently asked questions
Is claude-context or RAGLight more popular?
claude-context has 12,667 GitHub stars and RAGLight has 672. claude-context has the larger community by that measure.
Are claude-context and RAGLight free?
Both are open source. claude-context is licensed under MIT and RAGLight under MIT. Neither carries a licence fee.
What is the difference between claude-context and RAGLight?
claude-context is written in TypeScript and RAGLight in Python. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, claude-context or RAGLight?
Choose claude-context if you want the larger community (12,667 stars) or its MIT licence terms. Choose RAGLight if its feature set, stack or MIT licence fits better. Both are self-hostable.