M

MCP Qdrant Memory

An MCP memory server based on the Qdrant vector database, providing knowledge graph and semantic search capabilities.
2.5 points
34

What is MCP Memory Server with Qdrant Persistence?

The MCP Memory Server is a knowledge graph-based tool that represents knowledge through entities and relationships and provides powerful semantic search capabilities. It uses the Qdrant vector database for efficient similarity retrieval and supports file storage to ensure data persistence.

How to use MCP Memory Server with Qdrant Persistence?

First, you need to configure the environment variables, and then start the server to begin creating entities, adding relationships, and performing semantic searches. See the guide below for specific steps.

Applicable Scenarios

Suitable for application scenarios that require building complex knowledge graphs, such as recommendation systems, intelligent customer service, and academic research.

Main Features

Knowledge Graph ConstructionSupports creating entities, defining relationships, and adding observation records to form a complete knowledge network.
Semantic SearchAchieves efficient semantic similarity retrieval through the Qdrant vector database to quickly locate relevant content.
Multi-Mode StorageCombines file storage with a vector database to ensure data security and retrieval efficiency.
HTTPS SupportCompatible with the HTTPS protocol, facilitating deployment in a reverse proxy environment.

Advantages and Limitations

Advantages
Easy to build complex knowledge graphs
Powerful semantic search capabilities
Supports multiple storage methods, balancing performance and security
Compatible with the HTTPS protocol, facilitating deployment in a production environment
Limitations
Relies on external APIs (such as OpenAI), which may incur additional costs
May have performance bottlenecks when processing large-scale data

How to Use

Install Dependencies
Run the npm install command to install the dependencies required for the project.
Configure Environment Variables
Set the necessary environment variables, including the OpenAI API key and the Qdrant address.
Start the Server
Compile the project using the npm run build command and then start the service.

Usage Examples

Create a New EntityAdd a new entity node to the knowledge graph.
Perform a Semantic SearchFind the most relevant entities based on the input text.

Frequently Asked Questions

How to configure HTTPS support?
Does it support Docker deployment?
How to optimize search performance?

Related Resources

Official Documentation
Detailed installation guide and technical reference.
GitHub Repository
Source code repository. Contributions are welcome.
Video Tutorial
Quick start video.
Installation
Copy the following command to your Client for configuration
Note: Your key is sensitive information, do not share it with anyone.
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