Context Optimizer
Optimizes context for AI coding assistants by enabling them to extract targeted information from files and command outputs, rather than processing large data in its entirety.
About
The Context Optimizer is a powerful Model Context Protocol (MCP) server designed to enhance the efficiency of AI coding assistants like GitHub Copilot, Cursor AI, and Claude Desktop. By acting as an intelligent intermediary, it enables these AI tools to selectively extract crucial information from large files and terminal outputs, eliminating the need to process vast amounts of irrelevant data. This targeted approach significantly improves the relevance and accuracy of AI responses, providing developers with more precise assistance for coding tasks, file analysis, and even web research.
Key Features
- File Analysis Tool (askAboutFile)
- Robust Security Controls
- Terminal Execution & Extraction (runAndExtract)
- 3 GitHub stars
- Multi-LLM Support (Google Gemini, Claude, OpenAI)
- Web Research Capabilities (researchTopic, deepResearch)
Use Cases
- Executing terminal commands and analyzing their output with an LLM for targeted insights.
- Conducting focused web research to get current best practices or solve coding challenges.
- Extracting specific code snippets or information from large project files for AI assistants.
Advertisement