Contentful MCP Server
Enables fetching content types and entries from a Contentful CMS space, providing structured access to content management data.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Contentful MCP Servershow me all blog post entries from the last month"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Contentful MCP Server
A Model Context Protocol (MCP) server that allows Claude to interact with Contentful CMS data directly. This integration enables Claude to fetch content types and entries from your Contentful space.
Features
Fetch all content types from your Contentful space
Retrieve entries for specific content types
Structured responses for easy consumption by AI assistants
Related MCP server: microCMS MCP Server
Prerequisites
Node.js (v16 or higher)
A Contentful account with API keys
Claude Desktop (to use the MCP server with Claude)
Installation
Clone this repository:
git clone https://github.com/yourusername/contentful-mcp-server.git cd contentful-mcp-server
2.Install dependencies: npm install
Create a .env file in the root directory with your Contentful credentials: 4. CONTENTFUL_SPACE_ID=your_space_id CONTENTFUL_ACCESS_TOKEN=your_access_token CONTENTFUL_ENVIRONMENT=develop CONTENTFUL_PREVIEW_ACCESS_TOKEN=your_preview_token
npm run build
Or configure a build script in your package.json: "scripts": { "build": "tsc", "start": "node dist/index.js" }
##Configuration for Claude Desktop
{
"mcpServers": {
"contentful": {
"command": "node",
"args": [
"/absolute/path/to/contentful-mcp-server/dist/index.js"
]
}
}
}Available Tools
2 toolsget-content-typesC
get content types
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure but offers minimal information. 'Get content types' implies a read operation, but doesn't specify whether this requires authentication, what format the results will be in, whether there are rate limits, or any other behavioral characteristics. The description provides only the most basic functional information.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at just three words, but this brevity comes at the cost of being under-specified. While there's no wasted language, the description fails to provide sufficient context about what the tool does beyond the most basic level. It's appropriately sized for what it contains, but what it contains is inadequate.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there are no annotations, no output schema, and a sibling tool exists, the description is incomplete. For a tool that presumably returns content types, the description doesn't explain what format the results will be in, how they're structured, or how this differs from the 'get-entries' sibling tool. The minimal description leaves too many contextual questions unanswered.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters with 100% schema description coverage, so the baseline score is 4. The description doesn't need to explain parameters since none exist, and the schema fully documents this. No additional parameter information is required or expected in the description for this parameterless tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'get content types' is a tautology that essentially restates the tool name without adding meaningful context. It specifies the verb 'get' and resource 'content types', but lacks any distinction from sibling tools or clarification about what 'content types' refers to in this context. This minimal description provides only basic purpose information.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With a sibling tool 'get-entries' available, there's no indication of how these tools differ or when one should be preferred over the other. The description offers no context about appropriate use cases or prerequisites for this operation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get-entriesC
Get entries for a specific content type
| Name | Required | Description | Default |
|---|---|---|---|
| contentType | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states 'Get entries', implying a read operation, but doesn't disclose any behavioral traits such as permissions needed, rate limits, pagination, or what the return format looks like. This leaves significant gaps for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It is appropriately sized and front-loaded, stating the core purpose directly. Every word earns its place, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a tool with 1 parameter, no annotations, and no output schema, the description is incomplete. It doesn't explain what 'entries' are, how they are returned, or any behavioral aspects. This is inadequate for a tool that likely returns data, as users need more context to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter with 0% description coverage, and the description adds minimal meaning. It mentions 'content type' as the parameter but doesn't explain what content types are available, their format, or examples. This fails to compensate for the low schema coverage, leaving the parameter poorly documented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool's purpose as 'Get entries for a specific content type', which is clear but vague. It specifies the verb 'Get' and resource 'entries', but lacks detail on what 'entries' are or how they relate to 'content type'. It distinguishes from sibling 'get-content-types' by focusing on entries rather than types, but the distinction is minimal.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description implies usage when entries for a content type are needed, but it doesn't specify prerequisites, exclusions, or context. With a sibling tool 'get-content-types', there's no mention of whether to use one before the other or in what scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
TDQS
The two tools have clearly distinct purposes: get-content-types retrieves metadata about content types, while get-entries fetches actual content entries for a specific type. There is no overlap or ambiguity between these operations.
Both tools follow a consistent verb_noun naming pattern with hyphens (get-content-types and get-entries). The naming is predictable and uniform across the set.
With only 2 tools, the server feels severely under-scoped for a Contentful MCP server, which typically involves content management operations like creating, updating, or deleting entries and content types. This minimal set limits functionality.
The toolset is significantly incomplete for a content management domain. It only provides read operations (get-content-types and get-entries), missing essential CRUD operations such as create, update, or delete for entries and content types, which are core to content management workflows.
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