The hardest part of working with scattered data usually isn't the analysis — it's the dozen different APIs, auth flows, and export formats you cross before you can even start. Anyquery collapses that step: it speaks one language, SQL, to everything from a CSV on disk to your Notion workspace, and it does so by reusing SQLite's mature query planner rather than reinventing one.
What Sets It Apart
- One SQL dialect over 40+ sources via a plugin registry, so joining a local Parquet file against a GitHub repo's issues is a single query, not a pipeline.
- It exposes itself as a Model Context Protocol server, which means an LLM agent can read your Notion, Todoist, or files through structured SQL calls instead of brittle scraping — the data stays queryable, not just dumped into a prompt.
- It also masquerades as a MySQL server, so existing BI tools and database clients connect to it with zero new drivers.
- Built on SQLite, it inherits a proven engine and full SQL semantics (joins, aggregates, window functions) rather than a limited query subset.
Who It's For
Great fit if you live in SQL and want one tool to interrogate personal apps, local files, and APIs — or if you're wiring an LLM to private data and want it asking precise questions instead of guessing. Look elsewhere if your data already sits in one warehouse where native SQL is faster, or if you need heavy analytical workloads: this is an integration and exploration layer, not a high-throughput OLAP database. As a solo-maintained AGPLv3 project, the long tail of integrations also varies in depth.
