weaviate-mcp

# Weaviate MCP Server <div align="center"> **Weaviate vector database integration for AI assistants via Model Context Protocol (MCP)** [](https://www.python.org/downloads/) [](https://opensource.org/licenses/MIT) _Developed and maintained by [Arclio](https://arclio.ai)_ - _Secure MCP service management for AI applications_ </div> --- ## 🚀 Quick Start Test the server immediately using the Model Context Protocol (MCP) Inspector, or install and run it directly. ### Option 1: Instant Setup with MCP Inspector (Recommended for Testing) ```bash # First, start a local Weaviate instance docker-compose -f docker-compose.weaviate.yml up -d # Then test with MCP Inspector npx @modelcontextprotocol/inspector \ -e WEAVIATE_URL="localhost" \ -e WEAVIATE_HTTP_PORT="8080" \ -e WEAVIATE_GRPC_PORT="50051" \ -e WEAVIATE_OPENAI_API_KEY="your-openai-api-key" \ -- \ uvx --from weaviate-mcp weaviate-mcp ``` Replace `your-openai-api-key` with your actual OpenAI API key. ### Option 2: Direct Installation & Usage 1. **Install the package:** ```bash pip install weaviate-mcp ``` 2. **Set Environment Variables:** ```bash export WEAVIATE_URL="localhost" export WEAVIATE_HTTP_PORT="8080" export WEAVIATE_GRPC_PORT="50051" export WEAVIATE_OPENAI_API_KEY="your-openai-api-key" ``` 3. **Run the MCP Server:** ```bash python -m weaviate_mcp ``` ### Option 3: Using `uvx` (Run without full installation) ```bash # Ensure WEAVIATE_* environment variables are set as shown above uvx --from weaviate-mcp weaviate-mcp ``` ## 📋 Overview `weaviate-mcp` is a Python package that enables AI models to interact with Weaviate vector databases through the Model Context Protocol (MCP). It acts as a secure and standardized bridge, allowing AI assistants to leverage Weaviate's powerful vector search and storage capabiliti…