Leveraging MCP for automating your daily routine. This article explores the Model Context Protocol (MCP) and demonstrates how to build a toolkit for analysts using it, including creating a local MCP server with useful tools and integrating it with AI tools like Claude Desktop.
This video course introduces DuckDB, an open-source database for data analytics in Python. It covers creating databases from files (Parquet, CSV, JSON), querying with SQL and the Python API, concurrent access, and integration with pandas and Polars.
A discussion post on Reddit's LocalLLaMA subreddit about logging the output of running models and monitoring performance, specifically for debugging errors, warnings, and performance analysis. The post also mentions the need for flags to output logs as flat files, GPU metrics (GPU utilization, RAM usage, TensorCore usage, etc.) for troubleshooting and analytics.
An in-process analytics database, DuckDB can work with surprisingly large data sets without having to maintain a distributed multiserver system. Best of all? You can analyze data directly from your Python app.
