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Context Optimizer Mcp Server

mcp-malaksedarous-context-optimizer-mcp-server · by malaksedarous

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.

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Install

$ agentstack add mcp-malaksedarous-context-optimizer-mcp-server

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

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](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](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](docs/tools.md) and [docs/guides/usage.md](docs/guides/usage.md).

Documentation

All documentation is organized under the docs/ directory:

| Topic | Location | Description | |-------|----------|-------------| | Architecture | docs/architecture.md | System design and component overview | | Tools Reference | docs/tools.md | Complete tool documentation and examples | | Usage Guide | docs/guides/usage.md | Complete setup and configuration | | VS Code Setup | docs/guides/vs-code-setup.md | VS Code specific configuration | | Troubleshooting | docs/guides/troubleshooting.md | Common issues and solutions | | API Keys | docs/reference/api-keys.md | API key management | | Testing | docs/reference/testing.md | Testing framework and procedures | | Changelog | docs/reference/changelog.md | Version history | | Contributing | docs/reference/contributing.md | Development guidelines | | Security | docs/reference/security.md | Security policy | | Code of Conduct | docs/reference/code-of-conduct.md | Community guidelines |

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](docs/reference/manual-testing-setup.md). This provides a workflow-based testing protocol that validates all tools through realistic scenarios.

For detailed testing setup, see [docs/reference/testing.md](docs/reference/testing.md).

Contributing

Contributions are welcome! Please read [docs/reference/contributing.md](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](docs/reference/code-of-conduct.md)
  • Security Reports: Follow [docs/reference/security.md](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

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.