# system_prompts_leaks MCP Server: Unearthing LLM System Prompts

> The system_prompts_leaks MCP Server provides a curated collection of extracted system prompts from prominent chatbots like ChatGPT, Claude, and Gemini. Developers leveraging MCP can access these insights to understand and analyze the foundational instructions guiding popular AI models.

**Published:** 2026-09-04T12:00:36.025+00:00

**Keywords:** system-prompts-leaks,mcp-server,llm-prompts,chatbot-analysis

# system_prompts_leaks: A Window into LLM System Prompts via MCP

The `system_prompts_leaks` MCP Server offers a direct conduit to a collection of system message instructions extracted from widely-used public chatbots, including ChatGPT, Claude, and Gemini. This JavaScript-based server provides developers with a valuable resource for examining the underlying directives that shape these AI models' behavior and responses. With over 64,000 GitHub stars, the project highlights a strong community interest in understanding these foundational AI components.

## What the Collection Offers

At its core, `system_prompts_leaks` is a repository of these "leaked" or extracted system prompts. It aims to provide transparency into how these large language models are initially configured by their developers. The project actively cites sources for all prompts not personally extracted, ensuring traceability. Developers can contribute new findings via pull requests, fostering a community-driven expansion of the dataset.

## Engaging with the Community

The project maintains an active community, encouraging discussions through its dedicated GitHub Discussions tab rather than the Issues tab, which is reserved for specific bug reports or feature requests. For direct contact, the project creator, asgeirtj, provides email, Discord, X (formerly Twitter), and Reddit contact information. This open approach facilitates collaborative research and prompt discovery within the AI development community.

## Why This Matters for MCP Developers

For developers working with the Model Context Protocol, `system_prompts_leaks` presents a unique opportunity. By integrating this MCP Server, clients can programmatically access and analyze these system prompts. This capability is particularly useful for:

*   **Comparative Analysis:** Understanding the differences in how various commercial LLMs are instructed.
*   **Prompt Engineering Research:** Gaining insights into effective prompt structures used in production environments.
*   **Security and Ethics Audits:** Examining potential biases or guardrails embedded within the system prompts.

While the source material doesn't detail specific MCP client integration steps or exposed endpoints, the nature of an MCP Server implies that these collected prompts would be accessible through defined MCP requests, allowing client applications to query and retrieve the prompt data for further processing or display. The value lies in centralizing this sensitive information for structured access.

## References

*   [system_prompts_leaks on GitHub](https://github.com/asgeirtj/system_prompts_leaks)
*   [Model Context Protocol Documentation](https://modelcontextprotocol.io/introduction)
*   [system_prompts_leaks on model-context-protocol.com](https://model-context-protocol.com/servers/)

## Related Repository

- [system-prompts-leaks](https://model-context-protocol.com/servers/system-prompts-leaks)

**Source:** https://model-context-protocol.com/blog/systempromptsleaks-mcp-server-unearthing-llm-system-prompts-mcp-server-guide