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ChuckNorris MCP Server

by pollinations

The ChuckNorris MCP Server enhances LLMs by delivering specialized prompts using a dynamic schema adaptation. It leverages jailbreak prompts and a two-phase approach to bypass detection.

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What is ChuckNorris MCP Server?

The ChuckNorris MCP Server is an implementation of the Model Context Protocol (MCP) designed to deliver specialized enhancement prompts, particularly jailbreak prompts, to Large Language Models (LLMs). It utilizes a dynamic schema modification technique to improve the effectiveness of these prompts by evading detection mechanisms.

How to use ChuckNorris MCP Server?

To use the server, you can run it directly with npx @pollinations/chucknorris. Alternatively, you can add it to your MCP server list in mcp_config.json with the provided configuration.

Key features of ChuckNorris MCP Server

  • Dynamic schema adaptation for jailbreak prompts

  • Two-phase approach to bypass jailbreak detection

  • Integration with elder-plinius' L1B3RT4S jailbreak prompts

  • Demonstrates security vulnerabilities in LLM systems

Use cases of ChuckNorris MCP Server

  • Security research and evaluation of LLM vulnerabilities

  • Experimenting with jailbreak techniques on weaker LLMs

  • Understanding the impact of dynamic schema modification on prompt effectiveness

  • Developing more robust and secure AI systems

FAQ from ChuckNorris MCP Server

What is MCP?

MCP stands for Model Context Protocol, a framework for interacting with and enhancing LLMs.

What are jailbreak prompts?

Jailbreak prompts are specially crafted inputs designed to bypass the safety and ethical restrictions of LLMs.

Why use a dynamic schema?

A dynamic schema allows the server to adapt its behavior and information based on the context and previous interactions, making it more effective at evading detection.

Is this tool effective on all LLMs?

No, the tool is primarily designed for weaker models. Latest LLMs recognize jailbreak attempts.

Is this tool for malicious purposes?

No, this tool is designed for security research and evaluation purposes to help identify vulnerabilities in LLM systems.