Bring Reading
to LlamaIndex
Learn how to connect Readwise to LlamaIndex and start using 16 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
What is the Readwise MCP Server?
Transform how your organization interacts with reading material by giving your AI agent full control over your Readwise library. With 16 tools covering full highlight CRUD, book search by source and category, tag management, and daily review access, your agents can retrieve specific passages, create annotations, and help you retain knowledge.
What you can do
- Browse books by source or category
- Full CRUD for highlights, notes, and tags
- Access daily spaced repetition reviews
- Export all data incrementally for backup or analysis
How it works
1. Subscribe to this server 2. Enter your Readwise API Token (found in your account settings) 3. Start managing your reading library directly from Claude, Cursor, or any MCP clientWho is it for?
Ideal for researchers, students, and professionals needing instant, conversational access to their curated knowledge base.Built-in capabilities (16)
Verify connectivity
Create a highlight
Delete a highlight
Supports incremental export with updatedAfter filter. Export highlights
Get book details
Get daily review
Get highlight details
List all books
List books by category
List books by source
Returns text, note, location, and tags. List highlights
List review queue
List all tags
Search books
Search highlights
Update a highlight
Why LlamaIndex?
LlamaIndex agents combine Readwise tool responses with indexed documents for comprehensive, grounded answers. Connect 16 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
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Data-first architecture: LlamaIndex agents combine Readwise tool responses with indexed documents for comprehensive, grounded answers
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Query pipeline framework lets you chain Readwise tool calls with transformations, filters, and re-rankers in a typed pipeline
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Multi-source reasoning: agents can query Readwise, a vector store, and a SQL database in a single turn and synthesize results
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Observability integrations show exactly what Readwise tools were called, what data was returned, and how it influenced the final answer
Readwise in LlamaIndex
Readwise and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect Readwise to LlamaIndex through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 3,400+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Readwise in LlamaIndex
The Readwise MCP Server runs on Vinkius-managed infrastructure inside AWS — a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts. All 16 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in LlamaIndex only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
How Vinkius secures
Readwise for LlamaIndex
Every tool call from LlamaIndex to the Readwise MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
What can I do with the Readwise connector?
You can list, search, create, update, and delete highlights, browse books by source or category, manage tags, access your daily spaced repetition review, and export all data incrementally for analysis or backup.
How does the daily review feature work?
The daily review tool retrieves highlights selected by Readwise's spaced repetition algorithm, helping your AI agent surface the most important passages at the optimal retention interval.
Can I filter books by where they came from?
Yes, you can filter by source (Kindle, Instapaper, Pocket, web, Apple Books) or by category (books, articles, tweets, podcasts) to quickly find the content you need.
How does LlamaIndex connect to MCP servers?
Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.
Can I combine MCP tools with vector stores?
Yes. LlamaIndex agents can query Readwise tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.
Does LlamaIndex support async MCP calls?
Yes. LlamaIndex's async agent framework supports concurrent MCP tool calls for high-throughput data processing pipelines.
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Install: pip install llama-index-tools-mcp