Building an MCP server so every AI client shares the same tools is a strategic move towards streamlining operations and enhancing efficiency. At Slopey Industries, we’ve developed a Model Context Protocol (MCP) server that lets multiple AI clients access and use the same resources seamlessly. This server wraps GPU status, image generation, and memory management into a single interface, ensuring consistency and reliability across different AI systems. In this post, I’ll dig into how we built it and the benefits it brings.
What the Model Context Protocol Buys You
The MCP provides a unified interface for various AI clients to interact with shared resources. It abstracts the underlying hardware and software complexities, letting us focus on building applications rather than re-implementing the same plumbing in every client. The key components we exposed include:
- GPU Status Management: The server reports availability and usage across lanes, so each client knows where to route work.
- Image Generation Services: Centralizing generation reduces redundancy and improves throughput across formats and pipelines.
- Memory Management: A shared memory store means context written by one client is recallable by the next.
How We Built It
Implementing the server involved designing the architecture, building the components, and testing under load:
- Architecture Design: We defined the components and their interactions up front, making sure the server could handle the expected concurrency.
- Tool Development: We wrote each tool — GPU status, generation, memory — behind a single protocol surface, mixing open-source libraries with custom code.
- Testing and Optimization: We profiled hot paths, found bottlenecks, and tuned until the latency was acceptable.
Why It’s Worth It
- Resource Sharing: Multiple clients share the same backends, cutting cost and duplication.
- Consistency: One interface means Claude, Cursor, and our own agents behave the same way against the same tools.
- Scalability: New backends slot in behind the protocol without touching client code.
Bottom line: One MCP server turns scattered, per-client integrations into a single shared toolbox — every client gets every capability the moment we ship it.