RLM - Recursive Language Models
Execute tasks with verified code execution via mcporter MCP bridge. RLM writes and executes Python code iteratively until producing verified answers, ensuring 100% accuracy for calculations and computations.
🚀 RLM executes tasks by writing and running Python code iteratively until it produces verified answers. Unlike standard AI responses, RLM computations are 100% accurate for calculations and data processing. It bridges language models with real code execution through the mcporter MCP bridge, ensuring reliable results every time.
💡 Perfect for calculations, data analysis, code generation, and complex problem-solving. Use RLM when you need guaranteed accuracy—whether analyzing datasets, performing math operations, or generating tested code. It's ideal for tasks where precision matters and manual verification would be time-consuming.
✨ RLM stands out by combining AI reasoning with verified execution, eliminating hallucinations in computational tasks. You get both intelligent problem-solving and bulletproof accuracy—the best of both worlds for technical work.
Requirements
MCP bridge for connecting language models to tools
Recursive Language Models package
Python runtime environment
API key for accessing language models via OpenRouter