Semantic Frame is a token-efficient semantic compression tool for numerical data, designed to convert raw data from sources like NumPy, Pandas, and Polars into concise natural language summaries. This enables integration with LLMs, like Claude and other MCP-compatible clients, for effective and reliable data analysis without overwhelming the model context window or risking hallucinations. Ideal for developers, data scientists, and AI practitioners who need deterministic, summarizable insights from structured numerical data for agent workflows, analytics, or reporting.
Visit Semantic Frame's official website for product details and getting started.
Comprehensive guide on how to use Semantic Frame with examples and API references.
Join discussions and ask questions related to Semantic Frame on GitHub.
Explore various examples and practical applications of Semantic Frame in real-world scenarios.