Deployment: Dockerfile and Smithery config

Dockerfile

@@ -0,0 +1,21 @@
+# Generated by https://smithery.ai. See: https://smithery.ai/docs/config#dockerfile
+FROM node:lts-alpine
+
+# Create app directory
+WORKDIR /app
+
+# Install app dependencies
+COPY package*.json ./
+RUN npm install --ignore-scripts
+
+# Copy source files
+COPY . .
+
+# Build the project
+RUN npm run build
+
+# Expose port if needed (optional)
+# EXPOSE 3000
+
+# Start the server
+CMD ["node", "dist/index.js"]

README.md

@@ -1,4 +1,5 @@
 # MLflow Prompt Registry MCP Server
+[![smithery badge](https://smithery.ai/badge/@B-Step62/mcp-server-mlflow)](https://smithery.ai/server/@B-Step62/mcp-server-mlflow)
 
 Model Context Protocol (MCP) Server for [MLflow Prompt Registry](https://mlflow.org/docs/latest/prompts), enabling access to prompt templates managed in MLflow.
 
@@ -63,3 +64,11 @@ Configure Claude for Desktop by editing `claude_desktop_config.json`:
 ```
 
 Make sure to replace the `MLFLOW_TRACKING_URI` with your actual MLflow server address.
+
+### Installing via Smithery
+
+To install MLflow Prompt Registry Server for Claude Desktop automatically via [Smithery](https://smithery.ai/server/@B-Step62/mcp-server-mlflow):
+
+```bash
+npx -y @smithery/cli install @B-Step62/mcp-server-mlflow --client claude
+```

smithery.yaml

@@ -0,0 +1,25 @@
+# Smithery configuration file: https://smithery.ai/docs/config#smitheryyaml
+
+startCommand:
+  type: stdio
+  configSchema:
+    # JSON Schema defining the configuration options for the MCP.
+    type: object
+    required: []
+    properties:
+      mlflowTrackingUri:
+        type: string
+        default: http://localhost:5000
+        description: URL to the MLflow tracking server hosting the prompt registry.
+  commandFunction:
+    # A JS function that produces the CLI command based on the given config to start the MCP on stdio.
+    |-
+    (config) => ({
+      command: 'node',
+      args: ['dist/index.js'],
+      env: {
+        MLFLOW_TRACKING_URI: config.mlflowTrackingUri
+      }
+    })
+  exampleConfig:
+    mlflowTrackingUri: http://localhost:5000