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:

npm install -g context-optimizer-mcp-server

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

export CONTEXT_OPT_LLM_PROVIDER="gemini"
export CONTEXT_OPT_GEMINI_KEY="your-gemini-api-key"
export CONTEXT_OPT_EXA_KEY="your-exa-api-key"
export CONTEXT_OPT_ALLOWED_PATHS="/path/to/your/projects"

3. Add to your MCP client configuration:

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

"context-optimizer": {
  "command": "context-optimizer-mcp"
}

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

# Run all tests (skips LLM integration tests without API keys)
npm test

# Run tests with API keys for full integration testing
# Set environment variables first:
export CONTEXT_OPT_LLM_PROVIDER="gemini"
export CONTEXT_OPT_GEMINI_KEY="your-gemini-key"
export CONTEXT_OPT_EXA_KEY="your-exa-key"
npm test  # Now runs all tests including LLM integration

# Run in watch mode
npm run test:watch

Manual Testing

For comprehensive end-to-end testing with an AI assistant, see the **Manual Testing Setup Guide**. This provides a workflow-based testing protocol that validates all tools through realistic scenarios.

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)