Deployment: Dockerfile and Smithery config

Dockerfile

@@ -0,0 +1,41 @@
+# Generated by https://smithery.ai. See: https://smithery.ai/docs/config#dockerfile
+# Use a Node.js 16 base image
+FROM node:16 AS build
+
+# Set the working directory inside the container
+WORKDIR /app
+
+# Copy package.json and package-lock.json files
+COPY package.json package-lock.json ./
+
+# Install dependencies
+RUN npm install
+
+# Copy the entire project
+COPY . .
+
+# Build the project
+RUN npm run build
+
+# Use a lightweight Node.js image for the production environment
+FROM node:16-slim AS production
+
+# Set the working directory inside the container
+WORKDIR /app
+
+# Copy built files from the build stage
+COPY --from=build /app/build /app/build
+
+# Copy node_modules from the build stage
+COPY --from=build /app/node_modules /app/node_modules
+
+# Expose any necessary ports
+EXPOSE 6333
+
+# Environment variables
+ENV QDRANT_URL=http://localhost:6333
+ENV EMBEDDING_PROVIDER=ollama
+ENV OLLAMA_URL=http://localhost:11434
+
+# Run the application
+CMD ["node", "build/index.js"]

README.md

@@ -1,4 +1,5 @@
 # MCP-Ragdocs
+[![smithery badge](https://smithery.ai/badge/@qpd-v/mcp-server-ragdocs)](https://smithery.ai/server/@qpd-v/mcp-server-ragdocs)
 
 A Model Context Protocol (MCP) server that enables semantic search and retrieval of documentation using a vector database (Qdrant). This server allows you to add documentation from URLs or local files and then search through them using natural language queries.
 
@@ -15,6 +16,15 @@ Current version: 0.1.6
 
 ## Installation
 
+### Installing via Smithery
+
+To install RAGDocs for Claude Desktop automatically via [Smithery](https://smithery.ai/server/@qpd-v/mcp-server-ragdocs):
+
+```bash
+npx -y @smithery/cli install @qpd-v/mcp-server-ragdocs --client claude
+```
+
+### Manual Installation
 Install globally using npm:
 
 ```bash

smithery.yaml

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+# 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:
+      - qdrantUrl
+    properties:
+      qdrantUrl:
+        type: string
+        description: The URL of your Qdrant instance. For local use http://localhost:6333
+      qdrantApiKey:
+        type: string
+        default: ""
+        description: Your Qdrant Cloud API key
+      embeddingProvider:
+        type: string
+        default: ollama
+        description: Embedding provider to use ('ollama' or 'openai')
+      ollamaUrl:
+        type: string
+        default: http://localhost:11434
+        description: URL of your Ollama instance
+      openaiApiKey:
+        type: string
+        description: Your OpenAI API key
+      embeddingModel:
+        type: string
+        default: ""
+        description: Model to use for embeddings
+  commandFunction:
+    # A function that produces the CLI command to start the MCP on stdio.
+    |-
+    config => ({ command: 'node', args: ['build/index.js'], env: { QDRANT_URL: config.qdrantUrl, QDRANT_API_KEY: config.qdrantApiKey, EMBEDDING_PROVIDER: config.embeddingProvider, OLLAMA_URL: config.ollamaUrl, OPENAI_API_KEY: config.openaiApiKey, EMBEDDING_MODEL: config.embeddingModel } })