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.
README
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
- Clone the repository:
git clone https://github.com/hadv/wisdomforge
cd wisdomforge
- Install dependencies:
npm install
- Create a
.envfile in the root directory based on the.env.exampletemplate:
cp .env.example .env
- Configure your environment variables in the
.envfile:
Required Environment Variables
Database Configuration
DATABASE_TYPE: Choose your vector database (qdrantorchroma)COLLECTION_NAME: Name of your vector collectionQDRANT_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 totrueto enable HTTP server modePORT: Port number for local development only (default: 3000). Not used in Smithery cloud deployment.
Example .env configuration for Qdrant:
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
- Build the project:
npm run build
AI IDE Integration
Cursor AI IDE
Add this configuration to your ~/.cursor/mcp.json or .cursor/mcp.json file:
{
"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 keyYOUR_COLLECTION_NAME: Your Qdrant collection nameYOUR_QDRANT_URL: Your Qdrant instance URLYOUR_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:
{
"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"
}
]
}
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