Readwise MCP Server for LangChainGive LangChain instant access to 16 tools to Check Readwise Status, Create Highlight, Delete Highlight, and more
LangChain is the leading Python framework for composable LLM applications. Connect Readwise through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
Ask AI about this App Connector for LangChain
The Readwise app connector for LangChain is a standout in the Productivity category — giving your AI agent 16 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MultiServerMCPClient({
"readwise-alternative": {
"transport": "streamable_http",
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
}
}) as client:
tools = client.get_tools()
agent = create_react_agent(
ChatOpenAI(model="gpt-4o"),
tools,
)
response = await agent.ainvoke({
"messages": [{
"role": "user",
"content": "Using Readwise, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
asyncio.run(main())
* 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
About 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.
LangChain's ecosystem of 500+ components combines seamlessly with Readwise through native MCP adapters. Connect 16 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
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
Who is it for?
Ideal for researchers, students, and professionals needing instant, conversational access to their curated knowledge base.The Readwise MCP Server exposes 16 tools through the Vinkius. Connect it to LangChain in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 16 Readwise tools available for LangChain
When LangChain connects to Readwise through Vinkius, your AI agent gets direct access to every tool listed below — spanning reading, spaced-repetition, highlights, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
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
Connect Readwise to LangChain via MCP
Follow these steps to wire Readwise into LangChain. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install langchain langchain-mcp-adapters langgraph langchain-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
python agent.pyExplore tools
Why Use LangChain with the Readwise MCP Server
LangChain provides unique advantages when paired with Readwise through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Readwise MCP tools with 500+ LangChain components
Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
Memory and conversation persistence let agents maintain context across Readwise queries for multi-turn workflows
Readwise + LangChain Use Cases
Practical scenarios where LangChain combined with the Readwise MCP Server delivers measurable value.
RAG with live data: combine Readwise tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Readwise, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Readwise tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Readwise tool call, measure latency, and optimize your agent's performance
Example Prompts for Readwise in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Readwise immediately.
"Find all my highlights related to 'stoicism' and summarize the key themes."
"List all the books I've saved from my Kindle library."
"Create a new highlight for 'The Almanack of Naval Ravikant' with the note: 'Crucial insight on leverage'."
Troubleshooting Readwise MCP Server with LangChain
Common issues when connecting Readwise to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersReadwise + LangChain FAQ
Common questions about integrating Readwise MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.