Contentful MCP. Manage content entries and assets from chat.
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Contentful. Connect your AI agent to Contentful's headless CMS to manage and generate structured content. Fetch existing entries, discover content models, list assets, and publish draft content directly from your chat interface.
Automate editorial workflows and query content schemas without writing backend code.
What your AI agents can do
Create entry
Drafts and saves a new piece of content into the system.
Get content type
Retrieves the full schema details for a specific content type.
Get entry
Fetches the details and full content of one specific record.
The agent creates new content drafts using create_entry or modifies existing content records with update_entry.
The agent queries the system to list all available content types (list_content_types) or retrieve the specific schema details for a type (get_content_type).
The agent fetches specific content records using get_entry or lists all entries in an environment using list_entries.
The agent lists all available media files (list_assets) or finds out which environments (like 'staging' or 'master') are available in the space.
The agent executes state transitions, moving a draft to live content using publish_entry or reverting it to a draft with unpublish_entry.
Ask AI about this MCP
Supported MCP Clients
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Contentful MCP Server: 12 Tools for Content Management
These tools give your AI agent direct, programmatic access to the Contentful API. Manage content records, assets, and schemas across your entire digital publishing workflow.
019d757acreate entry
Drafts and saves a new piece of content into the system.
019d757aget content type
Retrieves the full schema details for a specific content type.
019d757aget entry
Fetches the details and full content of one specific record.
019d757alist assets
Lists all available media files (images, videos, etc.) in the current content environment.
019d757alist content types
Retrieves a list of every defined content model available in the current space.
019d757alist entries
Gets a list of records in the current environment, useful for auditing content count.
019d757alist environments
Lists all deployment environments (e.g., 'staging', 'master') in the current content space.
019d757alist organizations
Lists all Contentful organizations accessible to the account.
019d757alist spaces
Shows all Contentful spaces connected to the account.
019d757apublish entry
Moves a draft content record to a live, published status.
019d757aunpublish entry
Reverts a currently published record back to a draft state.
019d757aupdate entry
Modifies the content or metadata of an existing record.
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 every call
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Make Your AI Do More
Start with Contentful, then connect any of our 4,700+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,700+ others, all in one place
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- Works with Claude, ChatGPT, Cursor, and more
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What you can do with this MCP connector
Contentful MCP Server - Manage Content Entries
Connect your AI agent directly to Contentful's headless CMS. You can manage and generate structured content—everything from drafting articles to publishing final versions—straight from your chat interface. You won't need to touch the Contentful UI or write any backend code to get this done.
Drafting and Modifying Entries
- You can draft and save new content using
create_entry. You'll also modify existing content records withupdate_entry.
Content Schema Discovery
- Your agent can list all available content models by calling
list_content_types. You can also pull the full schema details for a specific content type usingget_content_type.
Content Retrieval and Status Check
- You can fetch the details and full content of a single record with
get_entry. You'll also get a list of all records in an environment usinglist_entries.
Asset and Environment Discovery
list_assetsshows you all the media files—images, videos, etc.—in the current content environment. You can find out which contentful spaces are connected to your account usinglist_spaces, which organizations are available withlist_organizations, and what deployment environments (like 'staging' or 'master') are available in the space usinglist_environments.
Content Publishing Workflow
- The agent handles state changes. You can move a draft content record to a live, published status with
publish_entry. If you need to pull back a published record, you can revert it to a draft state usingunpublish_entry.
How Contentful MCP Works
- 1 1. Connect the Contentful MCP Server to your AI client and pass your Personal Access Token.
- 2 2. Tell your agent the action: 'Find all blog post entries in the 'Marketing' space.'
- 3 3. The agent calls
list_entries, and the server returns a list of entries the agent can then read, modify, or publish.
The bottom line is, your agent talks to Contentful via tools, so you don't have to jump between your chat and the CMS UI.
Who Is Contentful MCP For?
This is for the Technical Writer, the Content Strategist, and the Front-End Developer. If your job involves moving content from a draft idea to a published website, this tool saves hours of manual clicking. It gives your AI client direct access to the content pipeline.
Outlines an article in the chat, and the agent automatically drafts and pushes the content into a new Contentful entry using create_entry.
Needs to know what content exists across different stages. They use the agent to list_entries across multiple spaces and check which are ready for review.
Needs to know the exact structure of a content type. They query the schema using get_content_type while building a front-end component.
What Changes When You Connect
- Automate the content lifecycle. Instead of manually copying text and updating records, let your agent
create_entrydrafts andupdate_entrycontent directly, treating the CMS like a chat variable. - Know the exact structure. When building a component, don't guess. Use
get_content_typeto query the schema details for any content type, guaranteeing your data matches the model. - Audit and locate content quickly. Use
list_environmentsto see if the content is in 'staging' or 'master', and thenlist_entriesto confirm the status of specific records. - Manage media without context switching.
list_assetsshows every image and file in the environment, so you can reference and include assets in drafts without leaving your planning window. - Control content status. Need to go live or pull back? Use
publish_entryto push a draft to production, orunpublish_entryif the content needs a quick rollback. - Discover everything available. Use
list_spacesandlist_content_typesto map out your entire content structure before you write a single word.
Real-World Use Cases
Publishing a Final Article
The technical writer finishes an article draft in the chat. They ask the agent to 'Publish the article 'AI Best Practices' now.' The agent calls publish_entry, moving the content from a draft state to live, published content instantly.
Updating a Schema for a New Feature
The developer needs to support a new metadata field on blog posts. They run get_content_type for 'Blog Post' to see the existing schema, identify the required field, and then manually guide the agent to update_entry with the new data structure.
Locating Specific Assets
A marketer needs a specific feature image. They ask the agent to list_assets and filter by file type. The agent returns the ID, which the marketer then uses in the chat to include the asset in a new draft.
Bulk Content Review
A content manager needs to review all drafts in a specific space. They use list_entries to get a count and list all drafts, allowing them to verify that the correct records were saved before publishing.
The Tradeoffs
Treating content like a simple database table
Asking the agent to just 'get all blog posts' without specifying the space or environment. This risks pulling mixed, stale data from development or staging environments.
→
Always scope the request. First, use list_spaces to identify the correct space, then list_environments to select the target environment, and finally list_entries to get the data. Never assume the default.
Publishing incomplete drafts
The agent successfully runs create_entry but the user forgets to update_entry the main body text. The content gets created but remains empty or unusable.
→
Always verify the schema first. Use get_content_type to confirm the required fields, then use create_entry only when all mandatory data points are ready to populate.
Mixing up assets and entries
The agent tries to 'update' an image using update_entry. This fails because images are handled by the asset system, not the entry data model.
→
Use list_assets to find the asset ID, and then include that ID reference when calling update_entry to properly link the image to the content record.
When It Fits, When It Doesn't
Use this server if your core job is managing structured, multi-stage digital content. You need to transition content from idea to published web asset using a defined workflow. If your process is simply 'store and retrieve unstructured text' (like a simple CRM note), this might be overkill. If your need is to manage a database with custom fields that aren't meant for public publishing, a dedicated backend tool might be better. You must use this when you need to know the schema (get_content_type) or when you need to control the content status (publish_entry, unpublish_entry). Don't use it just because it's an API; use it because you need the Contentful content lifecycle.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Contentful. 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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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 12 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Manually moving content from draft to live site is a painful, click-heavy process.
Today, a content writer writes an article, saves it as a draft in the CMS, copies the text, and then has to switch to a separate dashboard to find the correct space, confirm the content type, and manually hit the 'Publish' button. This is slow, and you often lose track of whether you updated the right version.
With this MCP server, your agent handles the whole thing. You tell it: 'Publish the article.' The agent calls `publish_entry`, confirming the content is live and visible. The whole process happens in the chat, no tabs needed.
Contentful MCP Server: Manage content entries and assets
You no longer have to guess what data fields exist. You simply ask the agent to `get_content_type` to see the exact schema, and then use that knowledge to `create_entry` a perfectly structured record.
This changes everything. You're working with a structured content model—the single source of truth—directly through conversation. It’s instant, and it's reliable.
Common Questions About Contentful MCP
How do I check what content types are available using list_content_types? +
Run list_content_types to get a list of every model in the current space. This shows you exactly what kinds of content you can create or retrieve.
What is the difference between get_entry and list_entries? +
get_entry fetches all the details for one specific content record, while list_entries returns a list of many records, usually just giving key identifiers and status.
Can I publish content using publish_entry if it's not finished? +
The system allows you to publish, but you should always review the content first. Use get_entry to fetch the draft and verify all sections are complete before calling publish_entry.
How do I find all the images I need for a new article using list_assets? +
Call list_assets to see all media files available in the environment. This gives you the IDs you need to reference when creating or updating an entry.
Does update_entry change the content status? +
No. update_entry only changes the content or metadata of an existing entry. You must call publish_entry separately to change its status from draft to live.
How do I manage different deployment environments using list_environments? +
list_environments lists all available environments (like 'master', 'staging', and 'development') for your space. You select the environment ID to ensure your AI agent operates on the correct data set.
What's the difference between get_content_type and list_content_types? +
list_content_types gives you a list of all available content types in the current space. get_content_type fetches the specific schema and details for one type you name.
Can I make changes to an entry using update_entry if I don't know the entry's ID? +
No, update_entry requires the specific entry ID you want to modify. First, use list_entries to get a list of entries, and then select the ID you need.
How do I generate a Contentful Personal Access Token? +
Log into your Contentful dashboard. Click on your profile picture in the top right corner and navigate to Account Settings. Locate Personal Access Tokens and click 'Generate Personal Token'. Copy the value provided.
Do I need the Space ID to use this integration? +
Yes. Most actions the AI performs require your specific Space ID to target the correct content repository effectively.
Can the agent interact with unpublished draft entries directly? +
Yes, Contentful's Content Management API (CMA) natively handles internal content regardless of publish state. You can command your AI to fetch, check, or structure a draft before hitting the publish flag explicitly.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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