Agentic systems like LangChain and LangGraph are powerful, but they need reliable tool access without a human in the loop. MCP is the right protocol for that, but actually deploying MCP servers was painful. Every one had different requirements (stdio vs HTTP), and scaling them in production was messy.

So we built NimbleTools Core:

* Team-Ready from Day One: multi-workspace support, RBAC, private registries.

* Universal Deployment: run stdio servers and HTTP servers with the same interface.

* Horizontal Scaling: MCP servers scale up/down automatically with demand.

* Community Registry: browse and deploy pre-configured servers, or publish your own.

* Kubernetes-Native: CRDs + operator pattern for lifecycle management.

Quick start (literally one command gets you running locally):

``` curl -sSL https://raw.githubusercontent.com/NimbleBrainInc/nimbletools... | bash ```

We’ve been using this for more complex customer deployments already, but wanted to give back by open-sourcing the core engine.

It’s still early — today NimbleTools Core gives you a solid runtime for deploying MCP servers on Kubernetes. Looking ahead, we’re experimenting with features outside the current MCP spec that we think will matter in production, like:

- Session management: keep context across multiple tool calls, not just one-off requests

- Smarter auto-scaling: more granular policies beyond just horizontal replicas

- Tool discovery & selection tools: helping agents automatically find, choose, and route to the right MCP server at runtime

We’d love feedback from the community on which direction matters most.

https://github.com/NimbleBrainInc/nimbletools-core

We just opened up a discord too (https://discord.gg/znqHh9akzj). Bit of a ghost town right now, but hoping to change that!