Contentful Delivery MCP Server
A Model Context Protocol (MCP) server that provides seamless access to Contentful’s Delivery API through AI assistants. Query and retrieve content entries, assets, and content types using natural language.
Quick Start
Install the package in your project:
npm install @mshaaban0/contentful-delivery-mcp-server
Or globally:
npm install -g @mshaaban0/contentful-delivery-mcp-server
Set up your Contentful credentials:
export CONTENTFUL_SPACE_ID="your_space_id"
export CONTENTFUL_ACCESS_TOKEN="your_access_token"
# Optional: Restrict content to specific content types
export CONTENTFUL_CONTENT_TYPE_IDS="blogPost,article,product"
Features
- Natural language queries to search content
- Retrieve entries by ID or content type
- Asset management
- Content type schema access
- Pagination support
- Rich text content handling
Available Tools
query_entries- Natural language search across all contentget_entry- Fetch specific entry by IDget_entries- List entries with filteringget_assets- Browse all assetsget_asset- Get asset details by IDget_content_type- View content type schemaget_content_types- List available content types
Integration with Mastra AI
Mastra AI provides seamless integration with this MCP server. Here’s how to set it up:
import { MastraMCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
// Initialize the MCP client
const contentfulClient = new MastraMCPClient({
name: "contentful-delivery",
server: {
command: "npx",
args: ["-y", "@mshaaban0/contentful-delivery-mcp-server@latest"],
env: {
CONTENTFUL_ACCESS_TOKEN: "your_access_token",
CONTENTFUL_SPACE_ID: "your_space_id",
// Optional: Restrict content to specific content types
CONTENTFUL_CONTENT_TYPE_IDS: "blogPost,article,product"
}
}
});
// Create an AI agent with access to Contentful
const assistant = new Agent({
name: "Content Assistant",
instructions: `
You are a helpful assistant with access to our content database.
Use the available tools to find and provide accurate information.
`,
model: "gpt-4",
});
// Connect and register tools
await contentfulClient.connect();
const tools = await contentfulClient.tools();
assistant.__setTools(tools);
// Example usage
const response = await assistant.chat("Find articles about machine learning");
Development
# Clone the repo
git clone https://github.com/mshaaban0/contentful-delivery-mcp-server.git
# Install dependencies
npm install
# Build
npm run build
# Development with auto-rebuild
npm run watch
# Run the inspector
npm run inspector
Debugging
The MCP Inspector provides a web interface for debugging:
npm run inspector
Visit the provided URL to access the debugging tools.
Resources
- Mastra AI Documentation
- Contentful API Reference
- MCP Specification
License
MIT
Contentful Delivery MCP Server
Project Details
- mshaaban0/contentful-delivery-mcp
- @mshaaban0/contentful-delivery-mcp-server
- MIT License
- Last Updated: 4/21/2025
Recomended MCP Servers
MCP server for OpenRouter.ai integration
MCP server for Coolify
MCP server for interacting with Prometheus
A Unity MCP server that allows MCP clients like Claude Desktop or Cursor to perform Unity Editor actions.
MCP server implementation for Google's Gemini API
MCP server for Directus API integration
MCP server that allows Claude to have a voice.
MCP server for Unreal Engine 5
ClickUp MCP Server - Integrate ClickUp task management with AI through Model Context Protocol
Allow AI to wade through complex OpenAPIs using Simple Language





