# Kontent.ai MCP

> 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.

## Overview
- **Category:** developer-tools
- **Price:** Free
- **Tags:** modular-content, api-driven, content-modeling, taxonomy, asset-management

## Description

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.

## Tools

### 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 you know its codename.

### list_content_types
Shows every defined content schema, allowing you to audit what types of content your project supports.

### get_content_type
Provides detailed metadata about a single content type, showing all its required fields and element options.

### 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 various filters.

### get_content_type_element
Gets specific metadata for an element within a type, useful when you need to know the options for a multiple-choice field.

## Prompt Examples

**Prompt:** 
```
List the last 10 content items in Kontent.ai
```

**Response:** 
```
I've retrieved the latest content items. Highlights include 'Homepage' (type: Page), 'Our Mission' (type: Article), and 'Product Catalog' (type: Catalog). Which one should I inspect for you?
```

**Prompt:** 
```
Show the schema for content type 'article'
```

**Response:** 
```
The 'Article' content type consists of: Title (text), Body (rich text), Author (taxonomy), and Publication Date (date). I can fetch specific articles of this type if you'd like.
```

**Prompt:** 
```
Search for items related to 'Winter Sale'
```

**Response:** 
```
Searching Delivery API… I found 2 items: 'Winter Sale Banner' and 'Promotion Rules'. I can retrieve the full content for either.
```

## Capabilities

### 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.

## Use Cases

### The product page needs a new field.
A developer realizes the Product Catalog type is missing a 'Warranty Info' field. Instead of emailing content ops, they ask their agent to run `list_content_types` and inspect the schema using `get_content_type`, immediately identifying the gap for the product owner.

### I need all articles mentioning a specific campaign.
A marketing specialist needs to pull every article related to 'Summer Sale.' They prompt their agent with a search query, which uses `search_kontent_ai` and returns a list of relevant codenames. The agent then fetches the full content for review.

### How do I find the right image?
A designer needs an asset from last year's campaign but can’t remember the file name. They use `list_content_assets` and filter by date range, getting a list of potential images they can then pass to their agent for retrieval.

### Mapping out content dependencies.
A data architect needs to know if the 'Article' type depends on a specific taxonomy group. They first use `list_taxonomies` and then drill down with `get_taxonomy_group` to map the exact relationships for their system.

## Benefits

- Stop logging into the Kontent UI just to check a schema. Use `list_content_types` or `get_content_type` to programmatically audit your entire content model with a single prompt.
- Need to find an image? Instead of navigating through file folders, use `list_content_assets` to query and locate specific media files directly from the MCP.
- Don't rely on memory for unique identifiers. Use `list_content_items` first to gather all necessary codenames before you attempt to pull down content using `get_content_item`.
- When building a site that relies heavily on classification, use the MCP to list taxonomy groups and map relationships across your data via `get_taxonomy_group`.
- Forget running simple keyword searches. Use `search_kontent_ai` to filter content using multiple parameters, dramatically improving search accuracy for agents.

## How It Works

The bottom line is that this MCP turns complex, siloed API calls into simple natural language instructions for your agent.

1. Subscribe to the MCP and provide your Project ID from Kontent.ai's settings.
2. If secure access is needed, input your Delivery API Key into the configuration panel.
3. Tell your agent what you need—for example, 'Audit all content types for me,' or 'Find assets related to Q4 promotions.' The MCP executes the query and returns structured data.

## Frequently Asked Questions

**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.