Context Optimizer MCP Server

Context Optimizer MCP Server

A Model Context Protocol (MCP) server that provides context optimization tools for AI coding assistants including GitHub Copilot, Cursor AI, Claude Desktop, and other MCP-compatible assistants enabling them to extract targeted information rather than processing large terminal outputs and files wasting their context.

This MCP server is the evolution of the VS Code Copilot Context Optimizer extension, but with compatibility across MCP-supporting applications.

🎯 The Problem It Solves

Have you ever experienced this with your AI coding assistant (like Copilot, Claude Code, or Cursor)?

• 🔄 Your assistant keeps compacting/summarizing conversations and losing a bit of the context in the process.
• 🖥️ Terminal outputs flood the context with hundreds of lines when the assistant only needs key information.
• 📄 Large files overwhelm the context when the assistant just needs to check one specific thing.
• ⚠️ "Context limit reached" messages interrupting your workflow.
• 🧠 Your assistant "forgets" earlier parts of your conversation due to context overflow.
• 😫 The reasoning quality drops when you have a longer conversation.

The Root Cause: When your assistant:

• Reads long logs during builds, tests, lints, etc. after executing a terminal command.
• Reads a large file (or multiple) in full just to answer a question when it doesn't need the whole code.
• Reads multiple web pages from the web to search a topic to learn how to do something.
• Or just during a long conversation.

The assistant will either:

• Start compacting, summarizing or truncating the conversation history.
• Drop the quality of reasoning.
• Lose track of earlier context and decisions.
• Become less helpful as it loses focus.

The Solution:

This server provides any MCP-compatible assistant with specialized tools that extract only the specific information you need, keeping your chat context clean and focused on productive problem-solving rather than data management.

Features

• 🔍 File Analysis Tool (askAboutFile) - Extract specific information from files without loading entire contents
• 🖥️ Terminal Execution Tool (runAndExtract) - Execute commands and extract relevant information using LLM analysis
• ❓ Follow-up Questions Tool (askFollowUp) - Continue conversations about previous terminal executions
• 🔬 Research Tools (researchTopic, deepResearch) - Conduct web research using Exa.ai's API
• 🔒 Security Controls - Path validation, command filtering, and session management
• 🔧 Multi-LLM Support - Works with Google Gemini, Claude (Anthropic), and OpenAI
• ⚙️ Environment Variable Configuration - API key management through system environment variables
• 🏗️ Simple Configuration - Environment variables only, no config files to manage
• 🧪 Comprehensive Testing - Unit tests, integration tests, and security validation

Quick Start

1. Install globally:

2. Set environment variables (see docs/guides/usage.md for OS-specific instructions):

3. Add to your MCP client configuration:

like "mcpServers" in claude_desktop_config.json (Claude Desktop) or "servers" in mcp.json (VS Code).

For complete setup instructions including OS-specific environment variable configuration and AI assistant setup, see docs/guides/usage.md.

Available Tools

• askAboutFile - Extract specific information from files without loading entire contents into chat context. Perfect for checking if files contain specific functions, extracting import/export statements, or understanding file purpose without reading the full content.
• runAndExtract - Execute terminal commands and intelligently extract relevant information using LLM analysis. Supports non-interactive commands with security validation, timeouts, and session management for follow-up questions.
• askFollowUp - Continue conversations about previous terminal executions without re-running commands. Access complete context from previous runAndExtract calls including full command output and execution details.
• researchTopic - Conduct quick, focused web research on software development topics using Exa.ai's research capabilities. Get current best practices, implementation guidance, and up-to-date information on evolving technologies.
• deepResearch - Comprehensive research and analysis using Exa.ai's exhaustive capabilities for critical decision-making and complex architectural planning. Ideal for strategic technology decisions, architecture planning, and long-term roadmap development.

For detailed tool documentation and examples, see docs/tools.md and docs/guides/usage.md.

Documentation

All documentation is organized under the docs/ directory:

Quick Links

• Get Started: See docs/guides/usage.md for complete setup instructions
• Tools Reference: Check docs/tools.md for detailed tool documentation
• Troubleshooting: Check docs/guides/troubleshooting.md for common issues
• VS Code Setup: Follow docs/guides/vs-code-setup.md for VS Code configuration

Testing

For detailed testing setup, see docs/reference/testing.md.

Contributing

Contributions are welcome! Please read docs/reference/contributing.md for guidelines on development workflow, coding standards, testing, and submitting pull requests.

Community

• Code of Conduct: See docs/reference/code-of-conduct.md
• Security Reports: Follow docs/reference/security.md for responsible disclosure
• Issues: Use GitHub Issues for bugs & feature requests
• Pull Requests: Ensure tests pass and docs are updated
• Discussions: (If enabled) Use for open-ended questions/ideas

License

MIT License - see LICENSE file for details.

Related Projects

• VS Code Copilot Context Optimizer – Original VS Code extension (companion project)