Advanced Model Context Protocol server enabling intelligent knowledge management, efficient retrieval, and storage of diverse domain insights using Qdrant or Chroma vector databases with seamless AI IDE integration.
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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.
git clone https://github.com/hadv/wisdomforge cd wisdomforge
npm install
.env
file in the root directory based on the .env.example
template:cp .env.example .env
.env
file:DATABASE_TYPE
: Choose your vector database (qdrant
or chroma
)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)HTTP_SERVER
: Set to true
to 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
npm run build
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 keyNote: 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.
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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