Readwise Vector DB FAQs

Question 1

What is Readwise Vector DB?

Accepted Answer

Readwise Vector DB is a self-hosted tool designed to transform your entire Readwise library into a semantically searchable vector database, making your highlights easily retrievable and usable.

Question 2

How does Readwise Vector DB integrate with AI/LLMs?

Accepted Answer

It features a streaming MCP (Message Communication Protocol) server, enabling direct and seamless integration with Large Language Model (LLM) clients. This allows LLMs to leverage your personal highlight library for enhanced context and advanced queries.

Question 3

Is Readwise Vector DB truly self-hosted, and what are the technical requirements?

Accepted Answer

Yes, it is entirely self-hosted. To run it, you'll need Python 3.12, Poetry (version 1.8+), Docker with Compose, and API keys for both Readwise and OpenAI for embeddings.

Question 4

What are the core features of Readwise Vector DB?

Accepted Answer

Its core features include self-hosted semantic search for Readwise highlights, automated nightly synchronization of your library, a high-performance HTTP vector search API, a streaming MCP server for LLM client integration, and Prometheus metrics for monitoring.

Question 5

How does Readwise Vector DB keep my highlight library updated?

Accepted Answer

The tool supports automated nightly synchronization to fetch new highlights. Additionally, it offers CLI commands for first-time full back-fills and incremental syncs, ensuring your database remains up-to-date with your Readwise library.

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