Qdrant MCP Server
About
A Model Context Protocol (MCP) server implementation for RAG
Details
- License
- MIT license
Explore
- Support for both Qdrant and Chroma vector databases
- Configurable database selection via environment variables
- Uses Qdrant's built-in FastEmbed for efficient embedding generation
- Domain knowledge storage and retrieval
- Documentation file storage with metadata
- Support for PDF and TXT file formats
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Qdrant MCP ServerCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
- Node.js 20.x or later (LTS recommended)
- npm 10.x or later
- Qdrant or Chroma vector database
node dist/index.js
Make the script executable:
chmod +x run-cursor-mcp.sh
Add this configuration to your ~/.cursor/mcp.json or .cursor/mcp.json file:
{
"mcpServers": {
"qdrant-retrieval": {
"command": "/path/to/your/project/run-cursor-mcp.sh",
"args": []
}
}
}
npm test
```
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"qdrant mcp server": {
"vito-mcp": {
"command": "node",
"args": [
"dist/index.js"
]
}
}
}
}McpServers
{
"vito-mcp": {
"command": "node",
"args": [
"dist/index.js"
]
}
}A server implementation that supports both Qdrant and Chroma vector databases for storing and retrieving domain knowledge.
Features
- Support for both Qdrant and Chroma vector databases
- Configurable database selection via environment variables
- Uses Qdrant's built-in FastEmbed for efficient embedding generation
- Domain knowledge storage and retrieval
- Documentation file storage with metadata
- Support for PDF and TXT file formats
Prerequisites
- Node.js 20.x or later (LTS recommended)
- npm 10.x or later
- Qdrant or Chroma vector database
Installation
1. Clone the repository:
git clone <repository-url>
cd qdrant-mcp-server
2. Install dependencies:
npm install
3. Create a .env file in the root directory based on the .env.example template:
cp .env.example .env
4. Update the .env file with your own settings:
DATABASE_TYPE=qdrant
QDRANT_URL=https://your-qdrant-instance.example.com:6333
QDRANT_API_KEY=your_api_key
COLLECTION_NAME=your_collection_name
5. Build the project:
npm run build
AI IDE Integration
Cursor AI IDE
Create the scriptrun-cursor-mcp.sh in the project root:
```bash
#!/bin/zsh
cd /path/to/your/project
source ~/.zshrc
nvm use --lts
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