Vinkius

Kontent.ai MCP. Audit content types and query structured data from anywhere.

Kontent.ai MCP connects your AI agent directly to Kontent.ai's Delivery API, giving you immediate access to structured content data. You can analyze entire content models, list every available content type and schema, query specific taxonomy groups, find assets in the library, or perform deep searches across your modular repository. Stop guessing what your content looks like; get a complete overview of your project's data structure from any compatible client.

Kontent.ai MCP is compatible with Claude Claude
Kontent.ai MCP is compatible with ChatGPT ChatGPT
Kontent.ai MCP is compatible with Cursor Cursor
Kontent.ai MCP is compatible with Gemini Gemini
Kontent.ai MCP is compatible with Windsurf Windsurf
Kontent.ai MCP is compatible with VS Code VS Code
Kontent.ai MCP is compatible with JetBrains JetBrains
Kontent.ai MCP is compatible with Vercel Vercel
See Vinkius in Action

Give Claude and any AI agent real-world access

Audit Content Schemas

Examine the full content types and schemas that define what kind of data exists within your repository.

Query Content Assets

Locate specific images, files, or other media stored in the centralized content library.

Map Content Relationships

Understand how your content is categorized by querying taxonomy groups and associated terms.

Retrieve Specific Content Details

Pull the full, modular details for any single article, product page, or piece of content using its unique codename.

Search Across Repository

Run filtered searches across your entire collection to find relevant items based on specific query parameters.

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AI Agent
Kontent.ai

What AI agents can do with Kontent.ai: 10 Tools for Content Modeling

These tools let you systematically audit your entire content repository structure, from listing every available item to deep-diving into specific data schemas and asset libraries.

Make your AI actually useful.

Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.

Start using Kontent.ai MCP

List Content Items

Lists all available content item codenames, helping you find the unique identifier for any article or page.

Get Content Item

Retrieves the full set of modular data fields and content for a specific item when...

List Content Types

Shows every defined content schema, allowing you to audit what types of content your...

Get Content Type

Provides detailed metadata about a single content type, showing all its required...

List Taxonomies

Lists every taxonomy group defined in your project's structure.

Get Taxonomy Group

Retrieves specific details about a single content classification group, including its terms and hierarchy.

List Project Languages

Lists all languages that are supported for content within your Kontent.ai project.

List Content Assets

Queries and lists every media asset, like images or files, stored in the library.

Search Kontent Ai

Performs a flexible search across your entire content delivery repository using...

Get Content Type Element

Gets specific metadata for an element within a type, useful when you need to know...

Security and governance baked right in.

Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.

Kontent.ai MCP is compatible with Claude

Claude AI

1

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.

2

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.

3

Start a conversation

Open a new chat. The Kontent.ai integration is available immediately — no restart needed.

Choose How to Get Started

Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.

Build Your Own

Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.

  • Import from OpenAPI, Swagger, or YAML specs
  • Create Agent Skills with progressive disclosure
  • Deploy to edge with MCPFusion framework
  • Built in DLP, auth, and compliance on each call
  • Real time usage dashboard and cost metering
  • Publish to catalog or keep private
Start building

Make Your AI Do More

Start with Kontent.ai, then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.

  • Use this MCP plus 5,200+ others, all in one place
  • Add new capabilities to your AI anytime you want
  • Connections are secured and governed automatically
  • Track usage and costs across all your servers
  • Works with Claude, ChatGPT, Cursor, and more
  • New servers added to the catalog weekly
Kontent.ai MCP server cover

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.

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The struggle to understand a CMS without developer access.

Today, if you need to know what fields are available on the 'Article' type—say, whether or not an author field is mandatory—you have to log into the Content Management System. You click through tabs, navigate schema views, and copy-paste names just to confirm a data point for a meeting. It's slow, it's prone to human error, and you can't automate the discovery process.

With this MCP, your agent handles that friction instantly. Instead of manual clicks, you prompt: 'Audit all content types.' The system immediately returns a clean, structured list of every schema and its fields. You get the data architecture overview in seconds.

Structured Content Discovery with Kontent.ai MCP

The biggest time sink is verifying content existence or structure. Checking if a product page codename exists, or confirming the required fields for a new article type, requires multiple manual steps across different backend tools.

Now, you can ask your agent to perform these checks in one go. By using `list_content_items` and then cross-referencing that list with schema details from `get_content_type`, you gain immediate data certainty. The entire process becomes a single conversation.

What Kontent.ai MCP does for your AI

Need to understand how complex structured content works? This MCP lets you connect your AI agent directly to Kontent.ai’s Delivery API, giving you full visibility into your modular content without ever touching the UI. Instead of sifting through dashboards or guessing what fields exist, you can ask your agent to audit your entire data model, listing all available schemas and their specific elements.

If you're building a site that needs structured, reliable content—think product pages with multiple variants, or complex articles requiring author attribution and date ranges—this is the connector for you. You can pull down all necessary metadata, from finding codenames using list_content_items to querying entire taxonomy groups. All of this powerful access lives within Vinkius, making it easy to plug Kontent.ai data into your agent workflow, regardless of whether you're working in Cursor or Claude.

Built · Hosted · Managed by Vinkius Kontent.ai MCP - Audit Structured Content & Schema Data
Server ID 019d75c2-f15e-737f-b478-5c7a7495bc61
Vinkius Inspector
Compliance Grade A+
Score 98.33/100
Vinkius Inspector Badge — Score 98.33/100

Frequently asked questions about Kontent.ai MCP

How do I check what content types are available using the Kontent.ai MCP? +

Run the list_content_types tool first. This will give you a complete list of every schema defined in your project, allowing you to see all possible content structures.

What is the difference between `get_content_item` and `search_kontent_ai`? +

list_content_items helps you find a specific item's unique codename. If you have that codename, use get_content_item to pull all its data. Use search_kontent_ai when you need to find multiple items based on keywords or filters.

Can I list the taxonomy groups using Kontent.ai MCP? +

Yes, use the list_taxonomies tool. This gives you an overview of all classification systems in your project, which helps map content relationships.

Does this MCP help me find images or files? +

You can find assets using list_content_assets. It queries the content library and returns a list of file metadata, so you know exactly what media is available.

What if I want to see the fields for 'product' type? +

You need to use get_content_type. If you provide the content type name, this tool returns all its specific elements and their options, letting you audit the schema.