An MCP server that uses Redis and in-memory caching to optimize and extend context windows for large chat histories
Overview
What is Context Optimizer MCP?
Context Optimizer MCP is a Model Context Protocol server that utilizes Redis and in-memory caching to optimize and extend context windows for large chat histories, enhancing the performance of chat applications.
How to use Context Optimizer MCP?
To use Context Optimizer MCP, you can install it via the MCP client, manually clone the repository, or use Docker. After installation, configure the server with your Anthropic API key and Redis settings, then start the server to begin optimizing chat contexts.
Key features of Context Optimizer MCP?
- Dual-Layer Caching: Combines fast in-memory LRU cache with persistent Redis storage.
- Smart Context Management: Automatically summarizes older messages to maintain context within token limits.
- Rate Limiting: Redis-based rate limiting with burst protection.
- API Compatibility: Drop-in replacement for Anthropic API with enhanced context handling.
- Metrics Collection: Built-in performance monitoring and logging.
Use cases of Context Optimizer MCP?
- Optimizing context for large-scale chat applications.
- Maintaining conversation continuity in customer support bots.
- Enhancing performance of AI-driven chat interfaces.
FAQ from Context Optimizer MCP?
- Can Context Optimizer MCP work with any chat application?
Yes! It is designed to be compatible with applications using the Anthropic API.
- Is there a limit to the number of messages it can handle?
The server optimizes context based on token limits, but it can handle large chat histories efficiently.
- How do I monitor performance?
The server includes built-in metrics collection for performance monitoring.