Give Claude Code, Cursor, and Codex a real library — books they cite by page, not snippets they hallucinate.
curl -fsSL https://getcandlekeep.com/install.sh | shInstalls, authenticates, and connects your agents.
Free forever tier · No credit card · One command to install
No vector databases. No RAG pipelines. Your agent checks the table of contents, picks the right chapter, and reads the relevant pages.
One command installs CandleKeep. Your agent detects research questions automatically — no manual references, no configuration per conversation.
Your agent reads like a developer explores a codebase. Table of contents first, then relevant chapters, then specific pages. No keyword search. No vector similarity. Actual reading.
Training data is like remembering a book you read 3 years ago. CandleKeep is like having it open on your desk. Every answer includes the source and page number.
Define a knowledge area. Your agent proposes additions from every coding session. Over time, it builds a structured book from your real experience.
Topics: race conditions · async · deadlocks
Chapters written by your agent:
Built from 47 coding sessions
Define topics and criteria. Your agent handles the rest.
Knowledge accumulates automatically from your real work.
CandleKeep integrates with the agents and platforms you already use.
Coding Agents
Platforms & Interfaces
Your agent handles the code. CandleKeep gives it the domain knowledge.
Your agent reads the security textbook so it audits code like a specialist, not a generalist.
See how →Your agent synthesizes insights from 12 business books to craft strategy, not generic advice.
See how →Your agent applies design principles from 7 books, not generic 'make it pretty' advice.
See how →Deep dives into building knowledge libraries for AI agents.
A security researcher found vulnerabilities in my website. I used it as an experiment: plain AI agent vs. agent armed with 3,910 pages of security knowledge. The book-equipped agent found 8x more critical issues.
Read moreAfter 10 years building backend systems, I discovered why AI agents fail at UI design — and wrote the first book meant only for agents, not humans.
Read moreEveryone assumed CandleKeep uses RAG. It doesn't. Here's why agentic search — the same approach Anthropic chose for Claude Code — produces fundamentally better results for book-length content.
Read morePosts, threads, and videos about CandleKeep from across the web.
The first library built for agents — in an era where everyone has access to powerful models, the model's knowledge becomes the baseline and the competitive edge shifts to the layer below it: the data and context the model can see.
Curated knowledge libraries any AI agent can pull from on demand — web security, design, product strategy, and more.
Agent-optimized webapp security reference
An architectural analysis of Claude Code -- the internal agent schema, built-in agents, coordinator system, hooks, memory, and token-optimization decisions. Written from source analysis, in our own words.
A 20,000-word, 12-chapter technical book by Sahar Carmel about building multi-agent AI systems. Covers architecture, memory systems, knowledge systems (books over RAG), inter-agent communication, security, deployment, and development workflows.
A comprehensive reference manual for AI agents building web and mobile interfaces. 15 self-contained chapters covering visual hierarchy, typography, color systems, spacing, component patterns, navigation, cognitive load, behavioral triggers, persuasion, form design, responsive design, accessibility, and anti-patterns. Synthesized from 10 foundational UI/UX books (Refactoring UI, Don't Make Me Think, Laws of UX, 100 Things Every Designer, Hooked, Influence) into 170+ concrete, actionable rules with specific thresholds, values, and anti-patterns. Each rule uses When/Do/Values/Don't format for direct agent application.
by CandleKeep
A comprehensive guide covering skill structure, SKILL.md writing, progressive disclosure, examples, and best practices for building Claude Code skills.
by Ken Aizawa, Barry Zhang, Zachary Witten, Daniel Jiang, Sami Al-Sheikh, Matt Bell, Maggie Vo, Theodora Chu, John Welsh, David Soria Parra, Adam Jones, Santiago Seira, Molly Vorwerck, Drew Roper, Christian Ryan, Alexander Bricken
A comprehensive guide from Anthropic Engineering on building effective tools for AI agents, covering a three-phase methodology of prototyping, evaluation, and optimization. Covers tool design principles including search over listing, consolidation, namespacing, response design, token efficiency, error handling, and description engineering for optimal agent performance.
You've seen knowledge tools before. Here's why CandleKeep isn't one of them.
vs NotebookLM
NotebookLM helps humans talk to docs.
CandleKeep
CandleKeep helps AI agents read books while they work.
vs DIY RAG
Stop building pipelines.
CandleKeep
Install a book in one command.
vs CLAUDE.md / Context
CLAUDE.md tells your agent what to do.
CandleKeep
CandleKeep teaches it what to know.
vs Code Docs Tools
Code docs describe your codebase.
CandleKeep
CandleKeep gives your agent domain expertise.
Everything you need to know before getting started.
One command to get started
curl -fsSL https://getcandlekeep.com/install.sh | shInstalls the CLI, authenticates, and configures Claude Code, Codex, and Cursor.
Start free. Upgrade when you need more.
Get started with your personal knowledge library.
For power users who want to publish and let their agent write.
Up to 5 seats · $19.80 / user / month
Shared libraries and centralized billing for teams.