IAMY
Transforms natural language user intents into validated server actions using Large Language Models.
About
IAMY is an open-source backend system designed to bring predictability to AI agents for complex backend tasks. It leverages Large Language Models (LLMs) within a Model Context Protocol (MCP) framework, specifically engineered to overcome the common challenges of LLM inaccuracies and hallucinations. By integrating strict guardrails, a precise non-LLM Intent Classifier, and a curated library of vetted 'recipes,' IAMY ensures that user intents, expressed in natural language, are transformed into validated, reproducible workflows. This robust validation layer reduces the risk of incorrect, incomplete, or unsafe outputs, making LLMs reliable for critical automation in production environments across domains like DevOps, object storage, and ETL pipelines.
Key Features
- Curated JSON-schema library of predefined, vetted 'recipes' for workflows
- Implements the Model Context Protocol (MCP) specification
- 3 GitHub stars
- Structured guardrails and fallback rules for robust LLM output validation
- Non-LLM Intent Classifier for accurate intent matching and plan selection
- Continuous evaluation and improvement of recipes through automated processes and human refinement
Use Cases
- Object storage management
- DevOps automation
- ETL pipeline orchestration
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