Install
$ agentstack add mcp-malaksedarous-context-optimizer-mcp-server ✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.
Security review
✓ PassedNo 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.
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 previousrunAndExtractcalls 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.mdfor complete setup instructions - Tools Reference: Check
docs/tools.mdfor detailed tool documentation - Troubleshooting: Check
docs/guides/troubleshooting.mdfor common issues - VS Code Setup: Follow
docs/guides/vs-code-setup.mdfor 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
- VS Code Copilot Context Optimizer – Original VS Code extension (companion project)
Source & license
This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: malaksedarous
- Source: malaksedarous/context-optimizer-mcp-server
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.