mcp-server-and-gw is an MCP gateway and server implementation designed to bridge AI models like Claude Desktop with external resources via HTTP SSE. It acts as a crucial intermediary, enabling AI models to access remote data sources and services, even if they lack native connection capabilities. This solution effectively translates between standard input/output and HTTP SSE endpoints, facilitating seamless communication.

Key features include easy installation via npm, direct execution with npx, and clear integration steps for Claude Desktop. Developers can leverage the example server and client for rapid prototyping and independent server development. By configuring Claude Desktop to use this gateway, AI models can discover and utilize a wider range of resources and tools. This enhances the AI's ability to interact with the external world, solving the common developer pain point of limited connectivity. Built with Node.js, mcp-server-and-gw offers a flexible and efficient solution for extending AI model functionality.

Stdio to HTTP/SSE Bridge

The mcp-server-and-gw acts as a crucial bridge, translating communication between AI models using standard input/output (stdio) and external services communicating over HTTP Server-Sent Events (SSE). This is particularly useful when AI models, like Claude Desktop, lack native support for direct HTTP connections. The gateway receives MCP requests via stdio, converts them into HTTP requests, and forwards them to the designated server. The server's SSE responses are then translated back into stdio for the AI model to process. This seamless translation enables AI models to interact with a wider range of external resources and tools without requiring modifications to the AI model itself.

For example, Claude Desktop, which primarily uses stdio for communication, can leverage this gateway to access a remote database server exposing its API via HTTP/SSE. The gateway handles the necessary protocol conversion, allowing Claude to query the database as if it were directly connected. The technical implementation involves parsing stdio input, constructing appropriate HTTP requests, handling SSE streams, and formatting the responses back into stdio.

Remote Resource Access

This gateway facilitates remote access to resources and tools for AI models. By acting as an intermediary, it allows AI models to interact with services hosted on different machines or behind firewalls. This is essential for scenarios where the AI model's execution environment is restricted or when the desired resources are only available remotely. The gateway securely forwards requests and responses, ensuring that the AI model can seamlessly utilize remote resources as if they were local.

Consider a scenario where an AI model needs to access a specialized data analysis tool running on a dedicated server. The mcp-server-and-gw enables the AI model to send requests to this tool, receive the results, and integrate them into its processing pipeline, all without needing direct access to the server's internal network. The gateway handles authentication and authorization, ensuring secure access to the remote resource. The implementation relies on establishing secure HTTP/SSE connections and managing the flow of data between the AI model and the remote server.

Simplified Integration

The mcp-server-and-gw simplifies the integration of AI models with the MCP ecosystem. It provides a standardized interface for communication, abstracting away the complexities of different transport protocols. This allows developers to focus on building and deploying AI models without worrying about the underlying communication infrastructure. The gateway handles the necessary protocol conversions and data formatting, ensuring seamless interoperability between different components of the MCP ecosystem.

For instance, a developer can easily integrate Claude Desktop with a custom tool by simply configuring the gateway to forward requests to the tool's HTTP/SSE endpoint. The gateway handles the translation between Claude's stdio-based communication and the tool's HTTP/SSE interface, eliminating the need for custom integration code. The implementation involves providing a configuration mechanism for mapping MCP requests to specific HTTP/SSE endpoints and handling the corresponding data transformations.

Technical Implementation

The mcp-server-and-gw is implemented in Node.js, leveraging its non-blocking I/O capabilities to efficiently handle concurrent requests. It utilizes standard libraries for HTTP/SSE communication and provides a simple command-line interface for easy deployment. The gateway is designed to be lightweight and portable, making it suitable for a variety of deployment environments. Its modular architecture allows for easy extension and customization to support different transport protocols and data formats. The core logic resides in src/mcp-server-and-gw.ts, which handles the protocol conversion and request routing. Example server and client implementations are provided in the examples directory for testing and demonstration purposes.