How to Use the Wiki.js MCP in CrewAI

Q: How do I search Wiki.js content using CrewAI?

You assign a 'Researcher' role and give it access to the searchpages tool. This agent gathers information, which then serves as shared memory for subsequent analysis agents.

Q: Can I create new wiki pages with Wiki.js and CrewAI?

Yes. You assign a 'Content Creator' role that uses the createpage tool. This allows your autonomous team to publish drafts based on research findings.

Q: Does the MCP Server support listing all Wiki.js pages with Wiki.js and CrewAI?

It does. An agent can run listpages to build a complete site map, which is then shared memory for other agents to check against.

Run autonomous Wiki.js research and documentation teams with CrewAI.

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Connect Wiki.js MCP to CrewAI

Create your Vinkius account to connect Wiki.js to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Wiki.js with CrewAI

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Autonomous Content Research

Set up a 'Researcher' agent that uses `search_pages` to gather all relevant information across the wiki. A separate 'Writer' agent can then take those findings and use `create_page` to draft new documentation. This simulates a full content audit cycle without needing human intervention at any step.

Multi-step Documentation Review

Need to change something? Assign an 'Editor' agent that checks the current page using `get_page`, and then assign an 'Implementer' agent to write the changes with `update_page`. The process flows from research to action. This role-based specialization ensures every part of the documentation update is handled by a specialized virtual team.

Full Wiki.js Site Mapping

Give your 'Monitor' agent the task of running `list_pages` to build an index, and then have another agent use that list to check for empty pages or missing categories (`delete_page`). It handles complex, hierarchical operations across the entire documentation set.

Setup guide

Set up Wiki.js 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 Wiki.js tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Wiki.js 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="Wiki.js Analyst",
        goal="Access and analyze Wiki.js data via MCP.",
        backstory="Expert analyst with direct Wiki.js access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Wiki.js 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 Wiki.js. 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 Wiki.js MCP in CrewAI

You assign a 'Researcher' role and give it access to the `search_pages` tool. This agent gathers information, which then serves as shared memory for subsequent analysis agents.

Yes. You assign a 'Content Creator' role that uses the `create_page` tool. This allows your autonomous team to publish drafts based on research findings.

Use a multi-agent workflow: one agent reads the existing content via `get_page`, and another writes the revised version using `update_page`. The collaboration ensures accuracy.

It does. An agent can run `list_pages` to build a complete site map, which is then shared memory for other agents to check against.

The server handles page paths and the body content of documents. This allows your CrewAI team to read, write, and structure complex documentation sets autonomously.

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