Memory MCP Server
The Memory MCP Server is a server that provides long-term memory functions for large language models (LLMs). By implementing the Model Context Protocol (MCP), it enhances the context awareness ability of LLMs in continuous interactions. The project provides a user-friendly API, supports storing and retrieving context information, is scalable, and is suitable for various LLM architectures.
rating : 2 points
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What is the Memory MCP Server?
The Memory MCP Server is a memory storage system specifically designed for AI chatbots. It enables AI to remember previous conversation content, just like humans having long-term memory, making AI responses more coherent and personalized.How to use the Memory MCP Server?
Through a simple API interface, developers can easily add memory functions to AI applications. Just a few lines of code are needed to store and retrieve conversation history.Applicable scenarios
It is particularly suitable for application scenarios such as AI assistants that require long-term memory, personalized customer service robots, and educational tutoring AIs.Main features
Long-term memory storageIt can permanently save the conversation history between AI and users, breaking through the short-term memory limitation of ordinary AIs.
Standard protocol supportIt adopts the general MCP protocol and is compatible with various AI models and frameworks.
Simple APIIt provides a concise RESTful API, which developers can quickly integrate.
High performanceIt is optimally designed to support high-concurrency requests and respond quickly.
Advantages and limitations
Advantages
Make AI conversations more coherent and natural
Support personalized user experiences
Open source and free, with community support
Easy to integrate into existing systems
Limitations
Requires additional server resources
Additional protection measures are needed for private data
Initial configuration may require technical support
How to use
Install the server
Clone the code repository and install the required dependencies.
Start the service
Run the server program.
Call the API
Interact with the server through HTTP requests.
Usage examples
Personalized customer service robotRemember users' previous consultation records and provide continuous services.
Educational tutoring AIRecord students' learning progress and weak points.
Frequently asked questions
What is the MCP protocol?
Where is the data stored?
Which AI models are supported?
Related resources
GitHub repository
Project source code and the latest version
MCP protocol documentation
Technical specifications of the Model Context Protocol
Usage tutorial video
Step-by-step teaching video
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