vito-mcp

# WisdomForge [](https://smithery.ai/server/@hadv/wisdomforge) A powerful knowledge management system that forges wisdom from experiences, insights, and best practices. Built with Qdrant vector database for efficient knowledge storage and retrieval. ## Features - Intelligent knowledge management and retrieval - Support for multiple knowledge types (best practices, lessons learned, insights, experiences) - Configurable database selection via environment variables - Uses Qdrant's built-in FastEmbed for efficient embedding generation - Domain knowledge storage and retrieval - Deployable to Smithery.ai platform ## Prerequisites - Node.js 20.x or later (LTS recommended) - npm 10.x or later - Qdrant or Chroma vector database ## Installation 1. Clone the repository: ```bash git clone https://github.com/hadv/wisdomforge cd wisdomforge ``` 2. Install dependencies: ```bash npm install ``` 3. Create a `.env` file in the root directory based on the `.env.example` template: ```bash cp .env.example .env ``` 4. Configure your environment variables in the `.env` file: ### Required Environment Variables #### Database Configuration - `DATABASE_TYPE`: Choose your vector database (`qdrant` or `chroma`) - `COLLECTION_NAME`: Name of your vector collection - `QDRANT_URL`: URL of your Qdrant instance (required if using Qdrant) - `QDRANT_API_KEY`: API key for Qdrant (required if using Qdrant) - `CHROMA_URL`: URL of your Chroma instance (required if using Chroma) #### Server Configuration - `HTTP_SERVER`: Set to `true` to enable HTTP server mode - `PORT`: Port number for local development only (default: 3000). Not used in Smithery cloud deployment. Example `.env` configuration for Qdrant: ```env DATABASE_TYPE=qdrant COLLECTION_NAME=wisdom_collection QDRANT_URL=https://your-qdrant-instance.example.com:6333 QDRANT_API_KEY=your_api_key HTTP_SERVER=true PORT=3000 # Only needed for local development ``` 5. Build the project: ```bash npm run build ``` ## AI IDE Integration ### Cursor AI IDE Add this configuration to your `~/.cursor/mcp.json` or `.cursor/mcp.json` file: ```json { "mcpServers": { "wisdomforge": { "command": "npx", "args": [ "-y", "@smithery/cli@latest", "run", "@hadv/wisdomforge", "--key", "YOUR_API_KEY", "--config", "{\"database\":{\"type\":\"qdrant\",\"collectionName\":\"YOUR_COLLECTION_NAME\",\"url\":\"YOUR_QDRANT_URL\",\"apiKey\":\"YOUR_QDRANT_API_KEY\"}}", "--transport", "ws" ] } } } ``` Replace the following placeholders in the configuration: - `YOUR_API_KEY`: Your Smithery API key - `YOUR_COLLECTION_NAME`: Your Qdrant collection name - `YOUR_QDRANT_URL`: Your Qdrant instance URL - `YOUR_QDRANT_API_KEY`: Your Qdrant API key Note: Make sure you have Node.js installed and `npx` available in your PATH. If you're using nvm, ensure you're using the correct Node.js version by running `nvm use --lts` before starting Cursor. ### Claude Desktop Add this configuration in Claude's settings: ```json { "processes": { "knowledge_server": { "command": "/path/to/your/project/run-mcp.sh", "args": [] } }, "tools": [ { "name": "store_knowledge", "description": "Store domain-specific knowledge in a vector database", "provider": "process", "process": "knowledge_server" }, { "name": "retrieve_knowledge_context", "description": "Retrieve relevant domain knowledge from a vector database", "provider": "process", "process": "knowledge_server" } ] } ```