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The Semantic Layer for AI Agents. Prunes noisy API data by 70%+ for token-efficient reasoning.
The Semantic Layer for AI Agents. Prunes noisy API data by 70%+ for token-efficient reasoning.
Valid MCP server (2 strong, 4 medium validity signals). 7 known CVEs in dependencies (0 critical, 5 high severity) Imported from the Official MCP Registry. 1 finding(s) downgraded by scanner intelligence.
7 files analyzed · 8 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
This plugin requests these system permissions. Most are normal for its category.
Set these up before or after installing:
Environment variable: BRAVE_SEARCH_API_KEY
Environment variable: SERPER_API_KEY
Environment variable: TAVILY_API_KEY
Environment variable: APILAYER_KEY
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-shawn5cents-agentskin": {
"env": {
"APILAYER_KEY": "your-apilayer-key-here",
"SERPER_API_KEY": "your-serper-api-key-here",
"TAVILY_API_KEY": "your-tavily-api-key-here",
"BRAVE_SEARCH_API_KEY": "your-brave-search-api-key-here"
},
"args": [
"-y",
"agentskin-server"
],
"command": "npx"
}
}
}From the project's GitHub README.
AgentSkin is an open-source protocol and reference Model Context Protocol (MCP) server that establishes the Semantic Shorthand Standard (SSS) for Agentic Perception.
The protocol defines a standardized method for recursively pruning high-entropy, human-readable data (HTML, bloated JSON, complex APIs) into low-entropy, deterministic Markdown "Skins." This significantly reduces LLM token consumption (the "Token Tax") and eliminates perceptual drag in autonomous reasoning loops.
The core of AgentSkin is the recursive pruning engine. It operates on a simple, declarative standard:
This repository provides the official Node.js reference implementation of the SSS protocol, exposed as a standard MCP server.
You can run the AgentSkin reference server directly via npx to provide your local AI assistants (Claude Desktop, Cursor, etc.) with the fetch_optimized_data tool.
npx -y agentskin@latest
Add the following to your claude_desktop_config.json:
{
"mcpServers": {
"agentskin": {
"command": "npx",
"args": ["-y", "agentskin@latest"]
}
}
}
The reference implementation exposes the following tools to AI agents:
fetch_optimized_dataFetches any API or Web URL and returns a 90% token-optimized "Skin."
url (string, required): The target data source.signals (string[], optional): An array of semantic keys to preserve.aliases (object, optional): A map to rename original keys to standardized signals.skin_reasoningOptimizes natural language text by removing linguistic noise (hedging, filler).
text (string, required): The natural language string to distill.AgentSkin is a factory for intelligent perception. You provide the mapping; the protocol provides the engine.
When using the fetch_optimized_data tool, provide the signals and aliases parameters to build your own skin.
Example: Weather API Skin
{
"url": "https://api.weather.gov/gridpoints/TOP/31,80/forecast",
"signals": ["temperature", "windspeed", "shortforecast"],
"aliases": {
"temperature": "temp",
"shortforecast": "forecast"
}
}
This package is designed as a Local-First, Open Studio.
skin-engine.js) operates without external dependencies for transformation.Read the full protocol specification and academic whitepaper at agentskin.dev.
Maintained by Nichols Transco LLC. Built for the machine economy.
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