How to Use the Readwise MCP in CrewAI

Q: Can Readwise and CrewAI automate my daily review process?

Absolutely. You can create a dedicated agent that calls getdailyreview every morning and sends the output to your preferred communication channel.

Q: How do I filter Readwise tool access for a CrewAI agent?

Use the toolfilter option in your agent config. This ensures your moderator agent only has access to write tools like updatehighlight while others remain read-only.

Deploy a specialized crew of agents in CrewAI to research, curate, and maintain your Readwise library autonomously.

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Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers — Included with Plan

Connect Readwise MCP to CrewAI

Create your Vinkius account to connect Readwise to CrewAI — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup Readwise with CrewAI

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Collaborative research teams

Assign a researcher agent to call `list_highlights` and feed the results to an analyst agent. They share memory to refine your knowledge base without you lifting a finger. This turns your library into an active asset. One agent finds the info, while the other puts it into context for your current projects.

Autonomous library maintenance

Set a monitor agent to watch your books using `list_books_by_category`. If it finds a new title, it can trigger a summary agent to process the content immediately. It keeps your library organized. The agents work in the background, ensuring your latest reads are always processed and categorized correctly.

Targeted highlight curation

Use `search_highlights` to let your agents find specific facts across your notes. They can cross-reference findings to answer complex questions about your reading history. It acts like a personal librarian. The agent digs through your saved content to surface exactly what you need for your current task.

Setup guide

Set up Readwise MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Readwise tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Readwise Analyst",
    goal="Access and analyze Readwise data via MCP.",
    backstory="Expert analyst with direct Readwise access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Readwise transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Readwise Analyst",
        goal="Access and analyze Readwise data via MCP.",
        backstory="Expert analyst with direct Readwise access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Readwise transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Readwise. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Readwise MCP in CrewAI

You pass the MCP server URL to your agent definition. You can filter the tools so that only the research agent gets access to `list_highlights` and `search_highlights`.

Absolutely. You can create a dedicated agent that calls `get_daily_review` every morning and sends the output to your preferred communication channel.

Yes. When one agent fetches data, the rest of the crew can reference those results in their own tasks, provided they are part of the same process.

Use the tool_filter option in your agent config. This ensures your moderator agent only has access to write tools like `update_highlight` while others remain read-only.

Your credentials are encrypted and scoped to your specific agent instance. Only the tools you explicitly authorize can access your highlights, tags, and book information.

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