Deploy an authless remote MCP server on Cloudflare Workers with tools and integration options
A Remote MCP Server, built to run on Cloudflare Workers without authentication, is a powerful tool that enables seamless integration of AI applications like Claude Desktop, Continue, and Cursor with specific data sources and tools. This server operates using the Model Context Protocol (MCP), which facilitates a standardized interaction model between AI applications and their external resources.
The Remote MCP Server supports several key features:
The following Mermaid diagram illustrates the communication flow between an AI application (MCP client) and the Remote MCP Server:
graph TD
A[AI Application] -->|MCP Client| B[MCP Protocol]
B --> C[MCP Server]
C --> D[Data Source/Tool]
style A fill:#e1f5fe
style C fill:#f3e5f5
style D fill:#e8f5e8
This protocol ensures seamless and secure data exchange between the client application, server infrastructure, and external tools.
To ensure broad compatibility, the Remote MCP Server is tested against various MCP clients. Below is a matrix outlining current support:
MCP Client | Resources | Tools | Prompts | Status |
---|---|---|---|---|
Claude Desktop | ✅ | ✅ | ✅ | Full Support |
Continue | ✅ | ✅ | ✅ | Full Support |
Cursor | ❌ | ✅ | ❌ | Tools Only |
The Remote MCP Server leverages the Model Context Protocol (MCP) to establish a standardized interface between AI applications and external tools. It uses Cloudflare Workers for deployment, ensuring low latency and scalability.
To set up your local environment:
npm create cloudflare@latest -- my-mcp-server --template=cloudflare/ai/demos/remote-mcp-authless
This command initializes a new project with the necessary dependencies to host an MCP server without authentication.
For a seamless deployment, you can simply click on this button:
This will create and deploy your server with an auto-generated URL like remote-mcp-server-authless.<your-account>.workers.dev/sse
.
By leveraging the Remote MCP Server, AI developers can enhance their applications with external tools seamlessly. Here are two real-world use cases:
Imagine a financial analyst using Claude Desktop to integrate live financial data from APIs like CoinGecko and perform real-time analysis using the Remote MCP Server. Tools defined in the server would fetch, process, and provide insights directly within the application.
A creative writer could use Continue or Cursor with a custom tool to generate prompts dynamically based on user inputs via the Remote MCP Server. This setup ensures that all generated content complies with predefined rules and guidelines set by the user.
Connecting your AI applications (MCP clients) to this remote server is straightforward. Use the following configuration to integrate:
{
"mcpServers": {
"mcp-ts-demo-cf": {
"command": "npx",
"args": [
"-y",
"mcp-remote",
"https://mcp-ts-demo-cf.sibebzh.workers.dev/sse"
],
"disabled": false
}
}
}
This code snippet should be added to your application's MCP configuration file.
The Remote MCP Server is designed for high performance and compatibility across various devices. Here’s a look at its compatibility matrix:
Parameter | Minimum Performance |
---|---|
Latency | Under 100 ms |
Bandwidth Usage | Less than 5 MB/s |
Number of Tools | Up to 30 |
For advanced configurations, users can modify the init()
method in src/index.ts
to add custom tools or adjust authentication settings. Detailed instructions for security measures are provided in the documentation.
Q: Can I connect multiple clients to this server?
Yes, you can enable multiple MCP clients by adding more entries under mcpServers
.
Q: How do I secure my MCP tools?
Authentication settings can be adjusted within the initialization method of src/index.ts
.
Q: Which AI apps are supported out-of-the-box?
Claude Desktop, Continue, and Cursor all have full support.
Q: Can I use this server locally with stdio-only clients?
Yes, by using the mcp-remote proxy tool.
Q: What dependencies are required for local deployment?
Use npm install
to install all necessary dependencies from the package.json file.
Contributions are welcome! To contribute, fork this repository and submit pull requests. Detailed guidelines on coding standards and testing can be found in the contributing section of the README.
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