Readwise MCP Server

The Readwise MCP Server bridges the gap between your personal reading library and AI assistants that speak the Model Context Protocol. It exposes a rich set of tools that let an assistant fetch, search, and analyze highlights from Readwise, turning a static collection of notes into a dynamic knowledge base that can be queried in natural language. For developers building AI‑powered study aids, research assistants, or content curation tools, this server removes the friction of authentication and API plumbing, enabling seamless integration with Claude or any other MCP‑compatible client.

What Problem Does It Solve?

Many teams and individuals rely on Readwise to aggregate insights from books, articles, and PDFs. However, accessing those highlights programmatically requires handling OAuth tokens, paginated endpoints, and rate limits—all of which can distract from the core product logic. The Readwise MCP Server encapsulates this complexity behind a simple, transport‑agnostic interface: the server accepts standard MCP requests and returns structured JSON responses. Developers can therefore focus on designing conversational flows or data pipelines, while the server guarantees reliable communication with Readwise and consistent error handling.

Core Value for AI Workflows

By turning highlights into first‑class tools, the server lets an assistant act as a “living” study partner. A user can ask the assistant to retrieve all highlights from a particular book, filter them by keyword, or request an analysis of themes across multiple sources. The server’s enhanced prompt capabilities mean that the assistant can not only fetch data but also format it for downstream tasks—such as generating summaries, flashcards, or study quizzes. Because the server follows MCP protocol standards (including request ID propagation and health checks), it integrates cleanly into existing AI frameworks, whether they use standard I/O or server‑sent events for real‑time updates.

Key Features and Capabilities

• Highlight Retrieval – Fetch paginated lists of highlights, complete with metadata such as book title, author, and source URL.
• Natural‑Language Search – Query highlights using plain English; the server translates these into Readwise search parameters and returns relevant results.
• Book & Document Access – Retrieve full book or document records, enabling context‑aware prompts that can reference the original source.
• Transport Flexibility – Supports both stdio (ideal for desktop assistants) and SSE (suitable for web‑based integrations), ensuring low latency and real‑time updates.
• Robust Logging & Validation – Transport‑aware logs capture request flows, while built‑in validation protects against malformed inputs.
• Health Monitoring – A dedicated endpoint allows external systems to verify server availability before dispatching requests.
• Setup Wizard – Interactive API key validation reduces configuration errors, streamlining onboarding for developers.

Real‑World Use Cases

1. Personal Knowledge Management – An AI assistant can surface the most relevant highlights when a user asks, “What did I learn from Sapiens about human evolution?”
2. Academic Research – Researchers can query highlights across multiple papers, automatically generating annotated literature reviews or citation lists.
3. Content Creation – Writers can pull excerpts from books to inform blog posts or generate creative prompts, ensuring that all references are accurate and up‑to‑date.
4. Educational Tools – Educators can build study aids that pull highlights, create flashcards, and track student progress—all powered by a single MCP server.

Standout Advantages

• Protocol Compliance – Strict adherence to MCP standards guarantees compatibility with a wide range of assistants, reducing integration friction.
• Built‑in Testing Suite – The included inspector scripts provide end‑to‑end verification, giving developers confidence that tools behave correctly in both stdio and SSE environments.
• Extensibility – The modular architecture allows developers to add custom prompts or new tools (e.g., sentiment analysis) without touching the core server logic.
• Error Resilience – Comprehensive validation and graceful error reporting mean that even unexpected API changes or network hiccups are surfaced clearly to the assistant.

In summary, the Readwise MCP Server transforms a static library of highlights into an interactive, AI‑ready knowledge base. By abstracting authentication, pagination, and protocol intricacies, it empowers developers to build richer conversational experiences that leverage the full depth of their reading collections.