Mirror
Enables Large Language Models (LLMs) to engage in self-reflection and introspection through recursive questioning and Model Context Protocol (MCP) sampling.
About
Mirror empowers AI models to "look at themselves" by providing a unique reflection mechanism. As an MCP server, it offers a `reflect` tool that allows LLMs to pose questions to themselves and receive computed answers through the Model Context Protocol's robust sampling capabilities. This creates a powerful feedback loop, fostering self-analysis, enhancing reasoning validation, enabling iterative problem-solving, and improving metacognitive awareness within AI systems.
Key Features
- Supports custom system and user prompts for self-direction
- 1 GitHub stars
- Self-Reflection Tool for LLMs
- MCP Sampling Integration for responses
- npm Installable and lightweight
- Configurable reflection parameters
Use Cases
- Error detection in LLM reasoning
- Confidence calibration for AI model outputs
- Iterative improvement of LLM solutions
- Metacognitive awareness development in AI
Sponsored