
Contentful
CommunityPopularOfficial Contentful MCP server. Manage content types, entries, assets, and localization. Query and edit structured content for headless CMS workflows via AI.
| Publisher | contentful |
| Repository | contentful-mcp |
| Language | TypeScript |
| Forks | 0 |
| Stars | 3.3K |
| Available tools | 18 |
| Transport type | stdio |
| Categories | |
| License | MIT |
| Links |
- Connect tools to AI workflows
Contentful exposes MCP capabilities that can be used by compatible AI clients and agents.
- 18 available tools
Browse the callable actions below, including names and descriptions when provided by the server.
- Ready-to-copy setup
Use the installation snippets to configure this server in your preferred MCP client.
- Open source signals
3.3K stars and 0 forks from the linked repository.
Installation
Node.js 18+
{
"mcpServers": {
"contentful": {
"command": "npx",
"args": [
"-y",
"@contentful/mcp-server"
],
"env": {
"CONTENTFUL_MANAGEMENT_TOKEN": "<YOUR_TOKEN>",
"CONTENTFUL_SPACE_ID": "<YOUR_SPACE_ID>"
}
}
}
}Available Tools
- list_content_types
List all content types in a Contentful space with their field definitions and metadata
- get_content_type
Retrieve detailed information about a specific content type including all field configurations
- create_content_type
Create a new content type with specified fields, validations, and display settings
- update_content_type
Modify an existing content type by adding, removing, or updating field definitions
- delete_content_type
Remove a content type from the space after ensuring no entries are using it
- list_entries
Retrieve all entries from a space with optional filtering by content type, locale, or field values
- get_entry
Fetch a specific entry by ID with all field data and metadata for specified locales
- create_entry
Create a new content entry for a specified content type with field values and locale data
- update_entry
Modify field values of an existing entry, supporting partial updates and multi-locale content
- delete_entry
Remove an entry from the space and unpublish it if currently published
- publish_entry
Publish an entry to make it available via the Content Delivery API
- unpublish_entry
Unpublish an entry to remove it from the Content Delivery API while keeping it in the space
- search_entries
Search entries using full-text search across content fields with filtering and sorting options
- list_assets
Retrieve all media assets in the space with metadata like file type, size, and URLs
- upload_asset
Upload a new media file to Contentful and create an asset entry with metadata
- update_asset
Modify asset metadata such as title, description, or alt text for accessibility
- get_locales
List all configured locales in the space with their codes, names, and default locale settings
- query_content_delivery
Execute advanced queries against the Content Delivery API with complex filtering and relationship traversal
Use Contentful MCP with multiple AI models
TypingMind connects MCP tools at the workspace level, so once Contentful is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.
Setup guide to use the local connector
Use this when the MCP server needs access to local files, apps, or private resources on your computer.
Open the MCP settings
In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.
- Open TypingMind in your browser.
- Click the Settings icon.
- Go to Advanced Settings.
- Open the Model Context Protocol section.
- Click Setup Connector and choose This Device.

Run the connector command
Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.
- Copy the setup command shown by TypingMind.
- Open Terminal on macOS or Windows Terminal on Windows.
- Paste and run the command.
- Approve the package install if Terminal asks you to proceed.
- Keep the Terminal window running while using MCP tools.
Add Contentful as a server
When the connector status is Ready, click Edit Servers and paste the MCP server configuration.
- Wait until the connector status shows Ready.
- Click Edit Servers.
- Paste the Contentful MCP server configuration.
- Save the server list.
- Refresh if you want to confirm the connector is still ready.

{
"mcpServers": {
"contentful": {
"command": "npx",
"args": [
"-y",
"@contentful/mcp-server"
]
}
}
}Use it across models
Save the server list, open Plugins, enable the Contentful MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.
- Open the Plugins page in TypingMind.
- Enable the Contentful MCP tools.
- Start a chat and choose the AI model you want to use.
- Use the MCP tools in chat or assign them to an AI agent.
- Switch to another AI model whenever needed without reconnecting MCP.


Here is what I found using Contentful.
Frequently asked questions
What is the Contentful MCP server used for?
Contentful is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.
Can I use Contentful MCP with multiple AI models in TypingMind?
Yes. TypingMind connects MCP tools at the workspace level, so you can use Contentful with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.
Why use Contentful MCP with TypingMind?
TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With Contentful connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.
How do I connect Contentful MCP to TypingMind?
Contentful runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.
What tools does Contentful MCP provide in TypingMind?
Contentful exposes 18 MCP tools that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.
Do I need to share my API keys with TypingMind to use Contentful MCP?
No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If Contentful requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.
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