How to Use the MediaWiki MCP in CrewAI

Q: How do I connect the MediaWiki MCP Server to a CrewAI agent?

Pass your Vinkius server URL directly into the agent's mcps array parameter. CrewAI handles the connection automatically, exposing all thirteen wiki tools to that specific agent.

Q: Can I restrict which CrewAI agents can edit MediaWiki pages?

Yes, you can use MCPServerHTTP from crewai.mcp with a toolfilter. This lets you give the writing agent access to editpage while keeping the research agent restricted to searchpages.

Deploy a crew of specialized CrewAI agents to research, write, and moderate your MediaWiki knowledge base autonomously.

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Connect MediaWiki MCP to CrewAI

Create your Vinkius account to connect MediaWiki 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 MediaWiki with CrewAI

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Coordinate multi-agent research on MediaWiki

The `search_pages` and `get_page_info` tools enable your CrewAI research agent to gather facts across your wiki. This agent can scan hundreds of articles, compile relevant summaries, and share its findings with other specialized agents in the crew. Because CrewAI uses shared memory, the entire team stays aligned on the research context. The research agent acts as the dedicated reader, feeding structured wiki data to the rest of the crew.

Automate content generation via this MCP Server

Our `edit_page` and `get_tokens` tools allow your writing agent to publish drafted content directly to the wiki. After the research agent finishes its analysis, the writer takes over, grabs the necessary tokens, and commits the edits. This division of labor keeps your agents focused on single tasks. The MCP Server manages the underlying API calls, making the transition from draft to published page completely autonomous.

Deploy a CrewAI team for wiki moderation

Using `list_recent_changes` and `get_page_revisions`, a moderator agent can monitor all recent edits on the platform. It analyzes the diffs for quality, while a separate coordinator agent decides whether to flag the changes for human review. This collaborative approach reduces errors and ensures high-quality contributions. You can run this entire operation headless in your CI/CD pipelines, keeping your wiki clean without constant manual oversight.

Setup guide

Set up MediaWiki 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 MediaWiki tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

Pass your Vinkius server URL directly into the agent's `mcps` array parameter. CrewAI handles the connection automatically, exposing all thirteen wiki tools to that specific agent.

Yes, you can use `MCPServerHTTP` from `crewai.mcp` with a `tool_filter`. This lets you give the writing agent access to `edit_page` while keeping the research agent restricted to `search_pages`.

The crew executes tasks sequentially or hierarchically. A manager agent ensures the research agent finishes analyzing the page before the writing agent calls `edit_page` to apply updates.

Yes, you can configure the MCP Server to point to any public or private MediaWiki instance. Just provide your custom API endpoint URL in the Vinkius configuration.

Your wiki contents and login tokens are processed entirely within Vinkius's zero-trust V8 sandbox. This ephemeral MCP Server model ensures no raw wiki data is ever cached or exposed to external networks.

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