Entroly Context Engine
Entroly is a high-performance context engineering engine that optimizes AI coding agent context windows through information-theoretic compression and reinforcement learning. It gives your AI 100% codebase visibility while reducing token consumption b
What is Entroly Context Engine?
Entroly Context Engine is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to entroly is a high-performance context engineering engine that optimizes ai coding agent context windows through information-theoretic compression and reinforcement learning. it gives your ai 100% code...
Entroly is a high-performance context engineering engine that optimizes AI coding agent context windows through information-theoretic compression and reinforcement learning. It gives your AI 100% codebase visibility while reducing token consumption b
This server falls under the Data Science & ML category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- Entroly is a high-performance context engineering engine tha
Use Cases
Maintainer
Works with
Installation
NPM
npx -y entroly-mcpManual Installation
npx -y entroly-mcpConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use Entroly Context Engine
Entroly is a high-performance context engineering engine that acts as an intelligent proxy between AI coding agents and LLM APIs, applying information-theoretic compression and reinforcement learning to reduce token consumption by 39-99% while giving agents full codebase visibility. It runs as an MCP server, an HTTP proxy, or a CLI wrapper and supports 38 AI coding tools including Claude Code, Cursor, Aider, and Copilot. Beyond compression, it includes WITNESS-based hallucination detection (AUROC 0.844), model routing, cache alignment, and response distillation.
Prerequisites
- Python 3.8+ (for pip install) or Node.js (for npm install)
- An AI coding agent or MCP client to wrap (Claude Code, Cursor, Aider, Copilot, etc.)
- Optional: ANTHROPIC_API_KEY or OPENAI_API_KEY if routing through those providers
- Optional: Rust toolchain for the native Rust engine (entroly[native] extras)
Install Entroly
Install Entroly using your preferred method. The core package includes the MCP server and Python compression engine. Use the full extras for all features.
# Core install (MCP server + Python engine):
pip install entroly
# Full install with all features:
pip install entroly[full]
# Or via npm (WASM runtime, no Python required):
npm install -g entroly
# Or via Homebrew:
brew install juyterman1000/entroly/entrolyAuto-Detect and Wrap Your Coding Agent
Navigate to your repository and run 'entroly go' to automatically detect your IDE/agent and apply context compression as a transparent wrapper.
cd /your/repo
entroly go
# Or target a specific agent:
entroly wrap claude-code
entroly wrap cursor
entroly wrap aiderOr Start the MCP Server
Run Entroly as a standalone MCP server for integration with MCP-compatible clients.
entroly serve
# Then configure your MCP client to connect to the serverConfigure as HTTP Proxy
Alternatively, run Entroly as an HTTP proxy on localhost:9377 and point your AI tool's base URL to it. The proxy transparently compresses outgoing context and intercepts responses.
entroly proxy
# Then set your tool's base URL:
export ANTHROPIC_BASE_URL=http://localhost:9377
export OPENAI_BASE_URL=http://localhost:9377/v1Configure Claude Desktop as MCP Client
Add Entroly to your Claude Desktop configuration to use it as an MCP server for context-optimized AI coding sessions.
{
"mcpServers": {
"entroly": {
"command": "npx",
"args": ["-y", "entroly-mcp"],
"env": {
"ANTHROPIC_BASE_URL": "http://localhost:9377",
"ENTROLY_LOCAL_NLI": "1"
}
}
}
}Entroly Context Engine Examples
Client configuration
Claude Desktop configuration for Entroly using the entroly-mcp npm package with optional local hallucination detection.
{
"mcpServers": {
"entroly": {
"command": "npx",
"args": ["-y", "entroly-mcp"],
"env": {
"ANTHROPIC_BASE_URL": "http://localhost:9377",
"ENTROLY_LOCAL_NLI": "1"
}
}
}
}Prompts to try
Commands and prompts for using Entroly's context compression and document analysis features.
- "Ingest all files in ./src and compress the context for my next coding session"
- "Select the most relevant context for the query: how does the authentication module work? Budget: 8000 tokens"
- "Show me the token savings from the last session"
- "Detect any potential hallucinations in this code explanation"Troubleshooting Entroly Context Engine
entroly go does not detect my IDE or coding agent
Use 'entroly wrap <agent>' to explicitly target your tool. Run 'entroly --list-agents' to see all 38 supported agents. If your agent is not listed, use the HTTP proxy mode with ANTHROPIC_BASE_URL or OPENAI_BASE_URL pointing to localhost:9377.
pip install entroly[native] fails on Apple Silicon or Windows
The native Rust engine requires a Rust toolchain. Install it with 'curl --proto "=https" --tlsv1.2 -sSf https://sh.rustup.rs | sh'. If you do not need the Rust engine, use 'pip install entroly' (Python engine only) or 'pip install entroly[full]' which falls back to Python if Rust compilation fails.
ANTHROPIC_BASE_URL proxy causes connection refused errors
Ensure 'entroly proxy' is running before starting your AI agent. The proxy starts on localhost:9377 by default. Verify it is running with 'lsof -i :9377' (macOS/Linux) or 'netstat -an | findstr 9377' (Windows). If the port is taken, configure an alternate port in the Entroly settings.
Frequently Asked Questions about Entroly Context Engine
What is Entroly Context Engine?
Entroly Context Engine is a Model Context Protocol (MCP) server that entroly is a high-performance context engineering engine that optimizes ai coding agent context windows through information-theoretic compression and reinforcement learning. it gives your ai 100% codebase visibility while reducing token consumption b It connects AI assistants to external tools and data sources through a standardized interface.
How do I install Entroly Context Engine?
Install via npm with the command: npx -y entroly-mcp. Then add the server configuration to your AI client's JSON config file (e.g., claude_desktop_config.json or .cursor/mcp.json).
Which AI clients work with Entroly Context Engine?
Entroly Context Engine works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is Entroly Context Engine free to use?
Yes, Entroly Context Engine is open source and available under the Apache-2.0 license. You can use it freely in both personal and commercial projects.
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Set Up Entroly Context Engine in Your Editor
Choose your AI client for step-by-step setup instructions.
Quick Config Preview
Add this to your claude_desktop_config.json or .cursor/mcp.json
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