productivity

Contentful (Official)

contentful

by contentful

Official Contentful integration for advanced content management software, automating full content lifecycle via Contentf

Official Contentful integration that enables full content lifecycle management including entries, content types, assets, environments, locales, tags, and automated content generation through Contentful's Content Management API with bulk operations and intelligent response handling.

github stars

46

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Official Contentful integrationSupports full content lifecycleBulk operations supported

best for

  • / Content managers maintaining Contentful spaces
  • / Marketing teams creating and updating campaigns
  • / Developers building content-driven applications
  • / Teams needing bulk content operations

capabilities

  • / Create and edit content entries
  • / Manage content types and fields
  • / Upload and organize assets
  • / Handle multilingual content and locales
  • / Perform bulk content operations
  • / Automate publishing workflows

what it does

Official Contentful integration that lets you manage content, assets, and workflows in Contentful spaces through natural language commands. Supports full content lifecycle operations including creation, editing, publishing, and bulk operations.

about

Contentful (Official) is an official MCP server published by contentful that provides AI assistants with tools and capabilities via the Model Context Protocol. Official Contentful integration for advanced content management software, automating full content lifecycle via Contentf It is categorized under productivity.

how to install

You can install Contentful (Official) in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

Contentful (Official) is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

Contentful MCP Server

A Model Context Protocol (MCP) server that provides AI assistants with comprehensive tools to interact with Contentful APIs.

🚀 Example Use Cases

This MCP server provides a comprehensive set of tools for content management, allowing AI to help you create, edit, organize, and publish content directly within Contentful. Once configured, you can use natural language in your AI assistant of choice to manage and interact with your Contentful spaces, including:

  • Content Creation: "Create a new blog post for our fall product launch"
  • Content Management: "Update all product entries to include the new pricing structure"
  • Asset Organization: "Upload and organize these marketing images by campaign"
  • Workflow Automation: "Create an AI action that translates content to Spanish"
  • Content Modeling: "Add a new field to the product content type for customer ratings"

📓 Table of Contents

⚙️ Getting started

Prerequisites

Installation

One-Click install

Install MCP Server

Note: This requires Cursor to be installed. If the link doesn't work, try the manual installation below.

Claude Desktop:

Download the .dxt configuration file here from the latest release and import it into Claude Desktop to automatically configure the MCP server with your environment variables.

Codex:

codex mcp add contentful --env CONTENTFUL_MANAGEMENT_ACCESS_TOKEN="your-CMA-token" --env SPACE_ID="your-space-id" --env ENVIRONMENT_ID="master" --env CONTENTFUL_HOST="api.contentful.com" -- npx -y @contentful/mcp-server

Install from source

git clone https://github.com/contentful/contentful-mcp-server.git
cd contentful-mcp-server
npm install
npm run build

Environment Variables

Environment VariableRequiredDefault ValueDescription
CONTENTFUL_MANAGEMENT_ACCESS_TOKEN✅ Yes-Your Contentful Management API personal access token
SPACE_ID✅ Yes-Your Contentful Space ID
ENVIRONMENT_ID❌ NomasterTarget environment within your space
CONTENTFUL_HOST❌ Noapi.contentful.comContentful API host
NODE_ENV❌ NoproductionNode Environment to run in

Configuration

Refer to the documentation for your AI tool of choice for how to configure MCP servers. For example, see the documentation for Codex, Cursor, VS Code, or Claude Desktop.

Below is a sample configuration:

{
  "mcpServers": {
    "contentful-mcp": {
      "command": "npx",
      "args": ["-y", "@contentful/mcp-server"],
      "env": {
        "CONTENTFUL_MANAGEMENT_ACCESS_TOKEN": "your-CMA-token",
        "SPACE_ID": "your-space-id",
        "ENVIRONMENT_ID": "master",
        "CONTENTFUL_HOST": "api.contentful.com"
      }
    }
  }
}

🛠️ Available Tools

CategoryTool NameDescription
Context & Setupget_initial_contextInitialize connection and get usage instructions
Content Typeslist_content_typesList all content types
get_content_typeGet detailed content type information
create_content_typeCreate new content types
update_content_typeModify existing content types
publish_content_typePublish content type changes
unpublish_content_typeUnpublish content types
delete_content_typeRemove content types
Entriessearch_entriesSearch and filter entries
get_entryRetrieve specific entries
create_entryCreate new content entries
update_entryModify existing entries
publish_entryPublish entries (single or bulk)
unpublish_entryUnpublish entries (single or bulk)
delete_entryRemove entries
Assetsupload_assetUpload new assets
list_assetsList and browse assets
get_assetRetrieve specific assets
update_assetModify asset metadata
publish_assetPublish assets (single or bulk)
unpublish_assetUnpublish assets (single or bulk)
delete_assetRemove assets
Spaces & Environmentslist_spacesList available spaces
get_spaceGet space details
list_environmentsList environments
create_environmentCreate new environments
delete_environmentRemove environments
Localeslist_localesList all locales in your environment
get_localeRetrieve specific locale information
create_localeCreate new locales for multi-language content
update_localeModify existing locale settings
delete_localeRemove locales from environment
Tagslist_tagsList all tags
create_tagCreate new tags
AI Actionscreate_ai_actionCreate custom AI-powered workflows
invoke_ai_actionInvoke an AI action with variables
get_ai_action_invocationGet AI action invocation details
get_ai_actionRetrieve AI action details and configuration
list_ai_actionsList AI actions in a space
update_ai_actionUpdate existing AI actions
publish_ai_actionPublish AI actions for use
unpublish_ai_actionUnpublish AI actions
delete_ai_actionRemove AI actions

🤝 Contributing

We welcome contributions! Please see our Contributing Guide for local development setup and contribution guide


FAQ

What is the Contentful (Official) MCP server?
Contentful (Official) is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Contentful (Official)?
This profile displays 26 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.8 out of 5—verify behavior in your own environment before production use.

Use Cases

Extended AI Capabilities

Add new capabilities to Claude beyond text generation

Example

Access external data sources, execute code, interact with tools and services

Transform Claude from chatbot to action-taking agent

Context Enhancement

Provide Claude with access to relevant context and data

Example

Load project documentation, access knowledge bases, query databases

Get more accurate, context-aware responses

Workflow Automation

Automate multi-step workflows combining AI and external tools

Example

Research → Summarize → Create document → Send notification

Complete complex tasks end-to-end without manual steps

Implementation Guide

Prerequisites

  • Claude Desktop 0.7.0+ or Cursor IDE with MCP support
  • Basic understanding of MCP architecture and capabilities
  • Access credentials for integrated services (if required)
  • Willingness to experiment and iterate on configuration

Time Estimate

15-60 minutes depending on server complexity

Installation Steps

  1. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 7.Document successful patterns for reuse

Troubleshooting

  • MCP server not loading: Check config syntax, verify installation
  • Connection errors: Check network, firewall, credentials
  • Feature not working: Read server docs, check required parameters
  • Performance issues: Monitor resource usage, check for network latency
  • Conflicts with other servers: Check port assignments, namespace collisions

Best Practices

✓ Do

  • +Read server documentation thoroughly before setup
  • +Start with simple use cases to validate functionality
  • +Test in non-production environment first
  • +Monitor resource usage and performance
  • +Keep servers updated for bug fixes and new features
  • +Document configuration for team members
  • +Use environment variables for sensitive configuration

✗ Don't

  • Don't grant overly permissive access to MCP servers
  • Don't skip reading security considerations in docs
  • Don't expose sensitive data without proper controls
  • Don't run untrusted MCP servers without code review
  • Don't ignore error messages—investigate root cause

💡 Pro Tips

  • Combine multiple MCP servers for powerful workflows
  • Create custom MCP servers for your specific needs
  • Share successful configurations with team
  • Use MCP inspector for debugging
  • Join MCP community for tips and troubleshooting

Technical Details

Architecture

Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

Protocols

  • Model Context Protocol (MCP)
  • JSON-RPC 2.0
  • stdio or HTTP transport

Compatibility

  • Claude Desktop
  • Cursor IDE
  • Custom MCP clients

When to Use This

✓ Use When

Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.

✗ Avoid When

Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.

Integration

  • Tool composition: Chain multiple MCP tools in workflows
  • Context augmentation: Provide AI with relevant external data
  • Action delegation: Let AI execute tasks on external systems
  • Bidirectional sync: Keep AI context and external systems in sync

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

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Ratings

4.826 reviews
  • Ganesh Mohane· Dec 24, 2024

    Contentful (Official) has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Evelyn Choi· Dec 16, 2024

    According to our notes, Contentful (Official) benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Yuki Yang· Dec 12, 2024

    Contentful (Official) reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Sakshi Patil· Nov 15, 2024

    Contentful (Official) reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Evelyn Perez· Nov 3, 2024

    Contentful (Official) has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Aditi Verma· Oct 22, 2024

    Contentful (Official) is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Chaitanya Patil· Oct 6, 2024

    We wired Contentful (Official) into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Aanya Liu· Sep 21, 2024

    We evaluated Contentful (Official) against two servers with overlapping tools; this profile had the clearer scope statement.

  • Ishan Abbas· Aug 12, 2024

    I recommend Contentful (Official) for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Yash Thakker· Jul 19, 2024

    According to our notes, Contentful (Official) benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

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