Model Context Gateway
Manages stateful, secure, and scalable conversation contexts for AI applications, overcoming Large Language Model memory limitations by storing individual user dialogue histories.
About
The Model Context Protocol (MCP) Server is engineered to address the inherent 'memorylessness' of Large Language Models (LLMs). It achieves this by maintaining distinct, persistent conversation contexts for each user, enabling AI to conduct consistent and personalized dialogues. This project serves as a comprehensive example of transforming an initial concept into a production-ready service, covering professional engineering practices from design and development to packaging, deployment, automation, and ongoing management.
Key Features
- 2 GitHub stars
- Stateful Conversation Management with Redis for persistent chat history.
- High-performance, asynchronous RESTful API developed with FastAPI.
- Automatic interactive Swagger/OpenAPI documentation generated from code.
- Containerized with Docker for portable and consistent deployment.
- CI/CD automation with GitHub Actions for automated deployment.
Use Cases
- Enabling consistent and personalized dialogues with Large Language Models.
- Managing persistent conversation history for AI-powered applications.
- Providing a scalable and secure gateway for LLM services in production environments.
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