How to Use the Kontent.ai MCP in CrewAI

Q: How do I perform a search in Kontent.ai with my CrewAI agents?

Give your agent the searchkontentai tool. It will use the provided query parameters to find relevant content items across your project during the execution of its task.

Q: Can CrewAI agents manage taxonomy groups in Kontent.ai?

They can. By calling listtaxonomies, agents gain visibility into your content classification. They use this information to organize or filter items during a collaborative project.

Q: Can my CrewAI agents see all languages in Kontent.ai?

Yes, they can. The listprojectlanguages tool allows your agents to check which locales are active. They can then select the correct language variant for their specific role.

Deploy autonomous content crews using this Kontent.ai MCP Server for CrewAI.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Kontent.ai MCP to CrewAI

Create your Vinkius account to connect Kontent.ai 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.

GDPR Free for Subscribers

Setup Kontent.ai with CrewAI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Specialized agent access for CrewAI

Assign specific tasks like `get_content_item` to your research agents. They pull the content while your writing agents process it independently. This separation of concerns makes your crews more efficient. One agent manages the retrieval, while the rest focus on analysis or transformation.

Hierarchical content inspection

Use `list_content_types` and `get_content_type_element` to give your crew a full map of your project. They learn the schema and adapt their behavior to match your CMS structure. It ensures your agents understand the data format before they act. They reference the metadata to avoid errors during content processing.

Autonomous content auditing

Set a monitor agent to use `list_content_items` on a schedule. It scans for new entries and alerts the rest of the crew to take action. It keeps your operations running without you. The crew detects updates and manages the workflow based on the live state of your CMS.

Setup guide

Set up Kontent.ai 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 Kontent.ai tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent Kontent.ai 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 Kontent.ai. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Kontent.ai now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Kontent.ai MCP in CrewAI

Give your agent the `search_kontent_ai` tool. It will use the provided query parameters to find relevant content items across your project during the execution of its task.

They can. By calling `list_taxonomies`, agents gain visibility into your content classification. They use this information to organize or filter items during a collaborative project.

Your data is kept within isolated sandboxes. Each request is ephemeral, meaning content is fetched only when the agent needs it and discarded immediately after.

It does. You can iterate through lists of items using the provided listing tools. Your agents process the data in batches to keep the workflow moving.

Yes, they can. The `list_project_languages` tool allows your agents to check which locales are active. They can then select the correct language variant for their specific role.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript