example: kind deployment

Makefile

@@ -30,10 +30,11 @@ clean:
 
 arm:
 	@echo "Building arm Docker image $(FULL_IMAGE_NAME)..."
-	docker build \
+	docker buildx build \
+		--platform linux/amd64,linux/arm64 \
 		-f $(DOCKERFILE_PATH) \
 		-t $(FULL_ARM_IMAGE) \
-		.
+		--load .
 	@echo "Docker image $(FULL_ARM_IMAGE) built successfully."
 
 .PHONY: all build push clean arm

README.md

@@ -176,6 +176,13 @@ mcpserver start -t http --port 8089 --config ./examples/jobspec/mcpserver.yaml
 
 We will provide examples for jobspec translation functions in [fractale-mcp](https://github.com/compspec/fractale-mcp).
 
+### Kubernetes (kind)
+
+This example is for basic manifests to work in Kind (or Kubernetes/Openshift). Note that we use the default base container with a custom function added via ConfigMap. You can take this approach, or build ON our base container and pip install your own functions for use.
+
+- [examples/kind](examples/kind)
+
+We will be making a Kubernetes Operator to create this set of stuff soon.
 
 ### Design Choices
 

examples/kind/README.md

@@ -0,0 +1,98 @@
+# HPC MCP Server Example
+
+> Run the mcpserver in Kubernetes (or OpenShift) with basic manifests
+
+## Prerequisites
+
+- [Docker](https://docs.docker.com/get-docker/)
+- [kind](https://kind.sigs.k8s.io/docs/user/quick-start/) (Kubernetes in Docker)
+- [kubectl](https://kubernetes.io/docs/tasks/tools/)
+- [Python 3.11+](https://www.python.org/downloads/) (for local testing)
+
+## 1. Create a Kind Cluster
+
+Start by creating a local Kubernetes cluster (with kind):
+
+```bash
+kind create cluster
+```
+
+## 2. Build and Load the Image
+
+Build the container image locally and load it into the `kind` nodes so you don't have to push to a remote registry.
+You can also pull and load.
+
+```bash
+# Build the image
+docker build -t ghcr.io/converged-computing/mcp-server:latest .
+
+# OR pull
+docker pull ghcr.io/converged-computing/mcp-server:latest
+
+# Load into kind
+kind load docker-image ghcr.io/converged-computing/mcp-server:latest
+```
+
+## 3. Deploy the Server
+
+The configuration and the custom tools are managed via a Kubernetes `ConfigMap`.
+This contains our `mcpserver.yaml` (the configuration) and `echo.py` (the tool code).
+
+```bash
+kubectl apply -f config-map.yaml
+```
+
+This launches the pod, mounts the configuration, and exposes it via a Service.
+
+```bash
+kubectl apply -f deployment.yaml
+kubectl apply -f service.yaml
+```
+
+Wait for the pod to reach the `Running` state:
+
+```bash
+kubectl get pods
+```
+
+See the server running:
+
+```bash
+kubectl logs mcp-server-5bbdcbbbdf-2sccc -f
+```
+
+Expose the service to your local machine:
+
+```bash
+kubectl port-forward svc/mcp-server-service 8080:80
+```
+
+Check health:
+
+```bash
+$ curl -s http://localhost:8080/health  | jq
+{
+  "status": 200,
+  "message": "OK"
+}
+```
+
+Ask for pancakes (you need fastmcp installed for this).
+
+```bash
+$ python3 get_pancakes.py 
+  ⭐ Discovered tool: pancakes_tool
+  ⭐ Discovered tool: simple_echo
+
+CallToolResult(content=[TextContent(type='text', text='Pancakes for Vanessa 🥞', annotations=None, meta=None)], structured_content={'result': 'Pancakes for Vanessa 🥞'}, meta=None, data='Pancakes for Vanessa 🥞', is_error=False)
+```
+
+Note that we can also run the server in stdio mode and then echo json RPC to it, but nah, don't really want to do that. 
+
+## Clean Up
+
+To delete the cluster and start over:
+
+```bash
+kind delete cluster
+```

examples/kind/config-map.yaml

@@ -0,0 +1,18 @@
+apiVersion: v1
+kind: ConfigMap
+metadata:
+  name: mcp-server-config
+data:
+  mcpserver.yaml: |
+    server:
+      transport: http
+      port: 8089
+      host: "0.0.0.0"    
+    tools:
+      - path: "custom_tools.echo.pancakes"
+        name: "pancakes_tool"
+
+  echo.py: |
+    from fastmcp import FastMCP
+    def pancakes(name: str = "Me") -> str:
+        return f"Pancakes for {name} 🥞"

examples/kind/deployment.yaml

@@ -0,0 +1,40 @@
+apiVersion: apps/v1
+kind: Deployment
+metadata:
+  name: mcp-server
+  labels:
+    app: hpc-mcp
+spec:
+  replicas: 1
+  selector:
+    matchLabels:
+      app: hpc-mcp
+  template:
+    metadata:
+      labels:
+        app: hpc-mcp
+    spec:
+      containers:
+      - name: mcp-server
+        image: ghcr.io/converged-computing/mcp-server:latest
+        imagePullPolicy: Always
+        args: ["--config", "/etc/mcp/mcpserver.yaml"]
+        ports:
+        - containerPort: 8089
+        env:
+        - name: PYTHONPATH
+          value: "/code:/mnt/custom"
+        volumeMounts:
+        - name: config-volume
+          mountPath: /etc/mcp/mcpserver.yaml
+          subPath: mcpserver.yaml
+        - name: tool-volume
+          mountPath: /mnt/custom/custom_tools/echo.py
+          subPath: echo.py
+      volumes:
+      - name: config-volume
+        configMap:
+          name: mcp-server-config
+      - name: tool-volume
+        configMap:
+          name: mcp-server-config

examples/kind/get_pancakes.py

@@ -0,0 +1,26 @@
+import asyncio
+from fastmcp.client.transports import StreamableHttpTransport
+from fastmcp import Client
+import sys
+import os
+
+
+port = 8080
+if len(sys.argv) > 1:
+    port = sys.argv[1]
+
+client = Client(f"http://localhost:{port}/mcp")
+
+async def call_tool(message: str):
+    async with client:
+        tools = await client.list_tools()
+        for tool in tools:
+            print(f"  ⭐ Discovered tool: {tool.name}")
+        print()
+        result = await client.call_tool("pancakes_tool", {"name": message})
+        print(result)
+
+try:
+    asyncio.run(call_tool("Vanessa"))
+except RuntimeError:
+    print("Please set the correct FRACTALE_MCP_TOKEN")

examples/kind/service.yaml

@@ -0,0 +1,49 @@
+---
+
+apiVersion: v1
+kind: Service
+metadata:
+  name: mcp-server-service
+spec:
+  selector:
+    app: hpc-mcp
+  ports:
+    - protocol: TCP
+      port: 80
+      targetPort: 8089
+  type: ClusterIP
+
+---
+
+apiVersion: v1
+kind: Service
+metadata:
+  name: mcp-server-headless
+spec:
+  clusterIP: None
+  selector:
+    app: hpc-mcp
+  ports:
+    - port: 8089
+      targetPort: 8089
+
+---
+
+# Ingress for external access (note requires an Ingress Controller like NGINX)
+apiVersion: networking.k8s.io/v1
+kind: Ingress
+metadata:
+  name: mcp-server-ingress
+  annotations:
+    nginx.ingress.kubernetes.io/rewrite-target: /
+spec:
+  rules:
+  - http:
+      paths:
+      - path: /mcp
+        pathType: Prefix
+        backend:
+          service:
+            name: mcp-server-service
+            port:
+              number: 80