Announcing new tools, apps, and regions for your real-world AI use cases
- July 29, 2025
- 2 min read
Three updates, one shared goal: helping builders move faster with AI. Our latest releases for Gcore Edge AI bring real-world AI deployments within reach, whether you’re a developer integrating genAI into a workflow, an MLOps team scaling inference workloads, or a business that simply needs access to performant GPUs in the UK.
MCP: make AI do more
Gcore’s MCP server implementation is now live on GitHub. The Model Context Protocol (MCP) is an open standard, originally developed by Anthropic, that turns AI models into agents that can carry out real-world tasks. It allows you to plug genAI models into everyday tools like Slack, email, Jira, and databases, so your genAI can read, write, and reason directly across systems. Think of it as a way to turn “give me a summary” into “send that summary to the right person and log the action.”
“AI needs to be useful, not just impressive. MCP is a critical step toward building AI systems that drive desirable business outcomes, like automating workflows, integrating with enterprise tools, and operating reliably at scale. At Gcore, we’re focused on delivering that kind of production-grade AI through developer-friendly services and top-of-the-range infrastructure that make real-world deployment fast and easy.”
— Seva Vayner, Product Director of Edge Cloud and AI, Gcore
To get started, clone the repo, explore the toolsets, and test your own automations.
Gcore Application Catalog: inference without overhead
We’ve upgraded the Gcore Model Catalog into something even more powerful: an Application Catalog for AI inference. You can still deploy the latest open models with three clicks. But now, you can also tune, share, and scale them like real applications.
We’ve re-architected our inference solution so you can:
- Run prefill and decode stages in parallel
- Share KV cache across pods (it’s not tied to individual GPUs) from August 2025
- Toggle WebUI and secure API independently from August 2025
These changes cut down on GPU memory usage, make deployments more flexible, and reduce time to first token, especially at scale. And because everything is application-based, you’ll soon be able to optimize for specific business goals like cost, latency, or throughput.
Here’s who benefits:
- ML engineers can deploy high-throughput workloads without worrying about memory overhead
- Backend developers get a secure API, no infra setup needed
- Product teams can launch demos instantly with the WebUI toggle
- Innovation labs can move from prototype to production without reconfiguring
- Platform engineers get centralized caching and predictable scaling
The new Application Catalog is available now through the Gcore Customer Portal.
Chester data center: NVIDIA H200 capacity in the UK
Gcore’s newest AI cloud region is now live in Chester, UK. This marks our first UK location in partnership with Northern Data. Chester offers 2000 NVIDIA H200 GPUs with BlueField-3 DPUs for secure, high-throughput compute on Gcore GPU Cloud, serving your training and inference workloads. You can reserve your H200 GPU immediately via the Gcore Customer Portal.
This launch solves a growing problem: UK-based companies building with AI often face regional capacity shortages, long wait times, or poor performance when routing inference to overseas data centers. Chester fixes that with immediate availability on performant GPUs.
Whether you’re training LLMs or deploying inference for UK and European users, Chester offers local capacity, low latency, and impressive capacity and availability.
Next steps
- Explore the MCP server and start building agentic workflows
- Try the new Application Catalog via the Gcore Customer Portal
- Deploy your workloads in Chester for high-performance UK-based compute
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Edge AI is your next competitive advantage: highlights from Seva Vayner’s webinar
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From budget strain to AI gain: Watch how studios are building smarter with AI
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Platforms that adopt scalable, adaptive moderation systems now will be better positioned to meet the next generation of content challenges without compromising on speed, safety, or user experience.Keep your streaming content safe and compliant with GcoreGcore Video Streaming offers AI Content Moderation that satisfies today’s digital safety concerns while streamlining the human moderation process.To explore how Gcore AI Content Moderation can transform your digital platform, we invite you to contact our streaming team for a demonstration. Our docs provide guidance for using our intuitive Gcore Customer Portal to manage your streaming content. We also provide a clear pricing comparison so you can assess the value for yourself.Embrace the future of content moderation and deliver a safer, more compliant digital space for all your users.Try AI Content Moderation for freeTry AI Content Moderation for free
Deploy GPT-OSS-120B privately on Gcore
OpenAI’s release of GPT-OSS-120B is a turning point for LLM developers. It’s a 120B parameter model trained from scratch, licensed for commercial use, and available with open weights. This is a serious asset for serious builders.Gcore now supports private GPT-OSS-120B deployments via our Everywhere Inference platform. That means you can stand up your own endpoint in minutes, run inference at scale, and control the full stack, without API limits, vendor lock-in, or hidden usage fees. Just fast, secure, controlled deployment on your terms. Deploy now in three clicks or read on to learn more.Why GPT-OSS-120B is big news for buildersThis model changes the game for anyone developing AI apps, platforms, or infrastructure. It brings GPT-3-level reasoning to the open-source ecosystem and frees developers from closed APIs.With GPT-OSS-120B, you get:Full access to model weights and architectureSelf-hosting for maximum data control and privacySupport for fine-tuning and model editingOffline deployment for secure or air-gapped useMassive cost savings at scaleYou can deploy in any Gcore region (or leverage Gcore’s three-click serverless inference on your own infrastructure), route traffic through your own stack, and fully control load, latency, and logs. This is LLM deployment for real-world apps, not just playground prompts.How to deploy GPT-OSS-120B with Gcore Everywhere InferenceGcore Everywhere Inference gives you a clean path from open model to production endpoint. You can spin up a dedicated deployment in just three clicks. We offer configuration options to suit your business needs:Choose your location (cloud or on-prem)Integrate via standard APIs (OpenAI-compatible)Control usage, autoscale, and costsDeploying GPT-OSS-120B on Gcore takes just three clicks in the Gcore Customer Portal.There are no shared endpoints. You get dedicated compute, low-latency routing, and full control and observability.You can also bring your own trained variant if you’ve fine-tuned GPT-OSS-120B elsewhere. We’ll help you host it reliably, close to your users.Use cases: where GPT-OSS-120B fits bestCommercial GPTs still outperform OSS models on some general tasks, but GPT-OSS-120B gives you control, portability, and flexibility where it counts. Most importantly, it gives you the ability to build privacy-sensitive applications.Great fits include:Internal dev tools and copilotsRetrieval-augmented generation (RAG) pipelinesSecure, private enterprise assistantsData-sensitive, on-prem AI workloadsModels requiring full customization or fine-tuningIt’s especially relevant for finance, healthcare, government, and legal teams operating under strict compliance rules.Deploy GPT-OSS-120B todayWant to learn more about GPT-OSS-120B and why Gcore is an ideal provider for deployment? Get all the information you need on our dedicated page.And if you’re ready to deploy in just three clicks, head on over to the Gcore Customer Portal. GPT-OSS-120B is waiting for you in the Application Catalog.Learn more about deploying GPT-OSS-120B on Gcore
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