Cloudflare API MCP Server is a lightweight Model Control Protocol (MCP) server deployed on Cloudflare Workers. It interfaces with the Cloudflare REST API and provides tools for managing DNS records, purging cache, listing zones, and more. It's designed to be simple and extensible, allowing developers to add new tools as needed.
The Cloudflare API MCP Server simplifies interactions with the Cloudflare API by providing an MCP interface. It allows users to manage Cloudflare resources like DNS records, caching, and other services programmatically through a lightweight server that runs on Cloudflare Workers. This makes it efficient, scalable, and easy to integrate into workflows using Cursor or other compatible platforms.
Developers, DevOps engineers, and IT professionals who work with Cloudflare services can benefit from this tool. It's particularly useful for those looking to automate tasks such as DNS management, cache purging, and zone listing via an MCP-compliant interface in their development environments or production systems.
The Cloudflare API MCP Server runs on Cloudflare Workers, which means it operates within Cloudflare’s global network infrastructure. This ensures low latency and high performance while interacting with the Cloudflare API directly from the edge locations.
You should consider using the Cloudflare API MCP Server when you need programmatic access to Cloudflare APIs in a structured way, especially if you're already leveraging MCP-based agents or tools like Cursor. It’s also ideal during local development or when deploying applications that require seamless integration with Cloudflare services.
To get started, clone the repository using the create-mcp CLI command provided in the documentation, upload your Cloudflare API credentials as secrets, and deploy the worker to your Cloudflare account. For local development, configure the .dev.vars file with your credentials and run `bun dev`.
Yes, you can extend its functionality by adding methods to the MyWorker class in the src/index.ts file. Each method corresponds to a new MCP tool that becomes available for use. Ensure proper JSDoc comments are included to define parameters and return values correctly.
Currently, the server supports tools for managing DNS records, purging cache, and listing zones. Future updates will include support for Workers, R2, KV, Queues, and Hyperdrive.
While the project is still under development, it can be used in production scenarios where its current capabilities meet your requirements. However, since it's actively being developed, ensure thorough testing before full-scale deployment.
MCP (Model Context Protocol) is an open protocol designed to standardize how applications provide context information to large language models (LLMs). Like a 'USB-C port' for AI applications, MCP ensures AI models can seamlessly connect with various data sources and tools.
An MCP Server is a server that supports the MCP protocol, enabling the exchange of contextual information between applications and AI models in a standardized way. It provides developers with an easy way to integrate AI models with databases, APIs, or other data sources.
An MCP Server eliminates the complexity of developing custom adapters by unifying the connection between AI models and various data sources. Whether you're a developer, data scientist, or AI app builder, an MCP Server simplifies the integration process, saving time and resources.
An MCP Server acts as an intermediary bridge, converting contextual information from various data sources into a format that AI models can understand. By adhering to the MCP protocol, it ensures data is transmitted between applications and AI models in a standardized manner.
At mcpserver.shop, you can browse our MCP Server Directory. The directory is categorized by industry (e.g., finance, healthcare, education), and each server comes with detailed descriptions and tags to help you quickly find the option that suits your needs.
The MCP Server Directory on mcpserver.shop is free to browse. However, some servers are hosted by third-party providers and may involve usage fees. Check the detailed page of each server for specific information.
MCP Servers support a wide range of data sources, including databases, APIs, cloud services, and custom tools. The flexibility of the MCP protocol allows it to connect almost any type of data source to AI models.
MCP Servers are primarily designed for developers, data scientists, and AI app builders. However, mcpserver.shop provides detailed documentation and guides to help users of varying technical levels get started easily.
Yes, MCP is an open-source protocol that encourages community participation and collaboration. For more details or to contribute, visit the official MCP documentation.
On mcpserver.shop, each MCP Server’s detailed page includes the provider’s contact information or a link. You can directly reach out to the provider for more details or technical support.