Any tool,
one fabric
NodeMode Dev Compute Solutions hosts Model Context Protocol servers on dedicated DGX B300 clusters, connecting the dots between your tools & the hardware that runs them.
We host MCP servers on named nodes, measured fabric, and power we can account for, bringing every tool to the client that calls it.
Managed servers
FabricPush a server, get an endpoint
GPU pools
PlacementShares, nodes & pods, priced
A hosted MCP server should be a normal server on a node you can name
Read the principles
2.3 TB
GPU memory per node
Eight 288 GB Blackwell Ultra GPUs, so weights stay resident & tools stay warm.
800 Gb/s
Per cluster port
Eight ConnectX-8 ports per node, wired to the GPUs over PCIe Gen6.
14.5 kW
Per node, N+N
Twelve front-loaded supplies; the node boots on three & runs redundant on six.
What a node server should be
A hosted MCP server should be boring. One endpoint, one schema the client can list, one node you can point at when someone asks where the call went.
Transports are not a feature. Streamable HTTP for the clients across the network, stdio for the one on your desk, & nothing invented in between.
A version is a version. When a server rolls back, its tool schemas & its secrets scope come back with it, or it did not roll back.
If a tool needs a GPU it should say which pool, how much of it, & what happens when the pool is full. The client should never find out by waiting.
How can we serve you?
Guides
What we are seeing, measuring & building in real time.
Guide
A hosted server is a normal server
The TypeScript SDK v2 in one file: McpServer, registerTool, a Standard Schema input, a stdio transport. Deploy the same file here & it answers over Streamable HTTP.
Figures
DGX B300, per node
Eight B300 GPUs, 2.3 TB of HBM3e, eight 800 Gb/s ports, 14.5 kW in 10 RU. Every figure from the NVIDIA user guide, with the power, thermal & port tables you need to plan a rack.
Read moreGuide
Which transport, & when
Streamable HTTP for remote clients, stdio for local ones. Both ship in the official SDKs, so a server written against the SDK runs on the fabric unchanged.
Read moreDeployment