The Memory MCP Server offers a robust solution for long-term memory management for Large Language Models, enabling them to retain and access context over prolonged interactions. It supports storing and retrieving memory data through API endpoints, improving the relevance and continuity of AI applications, especially in chatbots and virtual assistants.
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The Memory MCP Server offers a robust solution for long-term memory management for Large Language Models, enabling them to retain and access context over prolonged interactions. It supports storing and retrieving memory data through API endpoints, improving the relevance and continuity of AI applications, especially in chatbots and virtual assistants.
Added on:
Created by:
Apr 28 2025
Raffaello Ligustro William-2023.22.1584-11 IPA 1
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What is Memory MCP Server?
This MCP server implements the Model Context Protocol (MCP) to deliver long-term memory functionalities tailored for Large Language Models (LLMs). It allows developers to store contextual information associated with specific models and retrieve it later, ensuring sustained and coherent interactions. The server handles multiple requests, maintains data consistency, and adheres to MCP standards for seamless integration with various LLM architectures. Its scalable architecture supports growing data and interaction volumes, making it ideal for AI systems needing persistent memory capabilities across sessions.
Who will use Memory MCP Server?
- AI Developers
- LLM Integrators
- Chatbot Developers
- AI Researches
How to use the Memory MCP Server?
- Step1: Clone the repository from GitHub.
- Step2: Navigate to the project directory.
- Step3: Install dependencies with pip.
- Step4: Run the server using python app.py.
- Step5: Use provided API endpoints to store and retrieve memory data.
Memory MCP Server's Core Features & Benefits
The Core Features
- Store Memory via POST /store
- Retrieve Memory via GET /retrieve
- Supports long-term context storage
- Follows MCP standards
- Easy API integration
The Benefits
- Enhances context retention for LLMs
- Improves response relevance
- Scalable and reliable
- Supports seamless integration with existing systems
Memory MCP Server's Main Use Cases & Applications
- Long-term chatbot memory management
- Persistent context storage for AI assistants
- Long-duration conversational AI projects
FAQs of Memory MCP Server
Developer
- Sinhan88
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