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Query a CSV Folder with SQL — in Excel, Google Sheets, AI and REST

Query a folder of CSV files as one table. The agent works out the delimiter, encoding and columns for itself, then holds that shape steady so a bad export cannot quietly change your numbers.

Start free 13 destinations CSV Folder guide

One connection, every surface

Where your CSV Folder data can go

CSV Folder many files → one live table each
Federated queries + any other connector · one SQL across sources · every plan
Network Agent
  • 1 outbound connection
  • 0 inbound ports
  • read-only · files stay put

runs on

Query Streams turns a folder of CSV files into one live SQL table readable from Microsoft Excel, Google Sheets, AI assistants over MCP, the REST API and Power BI. The self-hosted agent samples the real files — delimiter, quote character, header row, encoding, date formats — pins that schema, then holds it: a later file that disagrees is held back and named in files_events, never silently loaded. Files stay on your machine; only query results leave the network.

One of 9 File Set drivers on one folder engine — the inventory tables, change trail and refusal rules under features are shared by the family CSV Folder File System Parquet Folder Excel Folder SQLite Folder JSONL Folder Multi-record CSV Machine Logs Web Server Logs

  1. For your team, vendors and partners

  2. CSV Folder to Excel Microsoft Excel · Excel add-in

    Pull live CSV Folder results straight into a worksheet and refresh them on demand — desktop Excel, Excel Online, Microsoft 365.

    How Excel works

  3. CSV Folder to Google Sheets Sheets add-on

    Run a saved CSV Folder query from the sidebar and drop the rows into the sheet. Shared collaborators can refresh it themselves.

    How Google Sheets works

  4. Ask Nova about CSV Folder Nova AI · text to SQL

    Ask a question in plain English. Nova already knows your CSV Folder tables, writes and runs the SQL, explains the answer and charts it — no query to write, no credentials to hand over.

    How Nova works

  5. CSV Folder to Data Viewer result sharing · team, vendors, partners · phone, tablet, desktop

    Share a live CSV Folder result with anyone — a colleague, a vendor, a partner — as a bookmarkable grid that re-runs fresh when opened, on a phone, a tablet or a desktop. They see the results, never the SQL or the files.

    How the Data Viewer works
  6. For apps and systems

  7. CSV Folder REST API HTTP endpoint

    Publish a CSV Folder query as an authenticated JSON endpoint any application can call, with an OpenAPI 3.1 spec and ready-made Postman, Insomnia and Hoppscotch collections. No database port is opened.

    How REST API works

  8. CSV Folder to Power BI Power Query M

    Paste the generated Power Query M into the Power BI Advanced Editor and the report reads live CSV Folder results over HTTPS — no ODBC driver, no database port opened.

    How Power BI works

  9. CSV Folder to Airtable Automation platform

    Sync CSV Folder rows into an Airtable base on a schedule, or fetch them inside an Airtable automation script.

    How Airtable works

  10. CSV Folder to Baserow Automation platform

    Feed a Baserow table from CSV Folder over the REST endpoint — self-hosted or Baserow cloud.

    How Baserow works

  11. CSV Folder to SeaTable Automation platform

    Keep a SeaTable base current with CSV Folder data without exporting a file or exposing the database.

    How SeaTable works

  12. CSV Folder to Smartsheet Automation platform

    Push CSV Folder results into a Smartsheet grid so plans and reports read from the source system, not last week's export.

    How Smartsheet works

  13. CSV Folder to Anvil Anvil Works · App platform

    Back an Anvil Python app with CSV Folder through the REST endpoint instead of embedding database credentials in the app.

    How Anvil works
  14. For AI tools

  15. CSV Folder MCP server Claude, Cursor and MCP clients

    Give an AI assistant read-only access to CSV Folder with the schema it needs to write correct SQL — no credentials in the chat.

    How MCP works
  16. Delivered to people

  17. CSV Folder alerts and reports Slack · Discord · Email · Webhook

    Put a CSV Folder query on a schedule and have the rows delivered to Slack, Discord, email or a signed webhook — or hold the message until a row count, threshold or percentage change crosses the line you set.

    How alerts and reports work

How it works

5 steps, no inbound firewall change

01

Install the Network Agent where it can see the folder — a shared drive, a nightly drop-folder, a department share.

02

Point the connector at it. Every .csv is matched, subfolders included, and you can narrow that with patterns.

03

On the first sync the agent samples the real files and works out the dialect itself: delimiter, quote character, header row, text encoding and date formats. That result becomes the table's fixed schema.

04

Every CSV is then read against that schema into one table, and each row carries a _source_file column naming the file it came from.

05

Query it. Treat the folder as one table, group by file to compare drops, or filter to a single file — all with ordinary SQL.

Feature deep-dive

What CSV Folder gives you

Where the columns come from

  • Sampled, not assumed — the agent inspects real files instead of trusting the first row of the first one.
  • Encodings handled — UTF-8, UTF-16, Windows-1252 and Latin-1, so accented names and European exports do not arrive as garbled text.
  • Money stays money — a column that always holds decimals is stored as an exact decimal, not a floating-point number, so totals do not drift by a cent.
  • A column only some files have becomes an empty column in the others, rather than a reason to fail.
-- The whole folder as one table, then per file
SELECT   _source_file, COUNT(*) AS rows, SUM(total) AS revenue
FROM     data
GROUP BY _source_file
ORDER BY revenue DESC

When a file disagrees

If the very first files contradict each other — two different delimiters, or a column that is a date in one file and free text in another — the connector refuses to pin anything and tells you which files and which columns disagree. It will not quietly pick a winner and let you find out at month end.

  • After that, one bad file is held back instead of corrupting the table: a changed header, an extra column, a value that does not fit, or a truncated last line.
  • Its rows stay out, and files_events records exactly which file and which column caused it.
  • Every other file in the folder still loads. One broken export never takes the report down.

One table, or one per layout

Recurring exports of the same report belong in a single table, and that is the default. If the folder genuinely holds different CSVs — a customer list sitting next to an order dump — switch to per-layout mode and each distinct layout gets its own table, up to 25 of them.

Shared by the whole File Set family

Every folder connector also gives you

  • files_current — a live inventory: every file the connector can see right now, with its path, size and modified date.
  • files_events — the audit trail: what appeared, what changed, what vanished, and anything held back, with the filename and the reason.
  • directories and volumes — per-folder totals, daily growth history, and how much room is left on the drive.
  • Only files that actually changed are re-read on each sync, so a folder of 50,000 files is not re-parsed because one new export landed.

Good to know

  • Read-only, enforced — one statement at a time, SELECT and friends only. Your files are never written, moved or renamed.
  • Nothing is uploaded — the data is cached, encrypted, on your own machine beside the agent. Only the result of a query leaves your network.
  • Sensible defaults — up to 250,000 files, 16 folders deep, 512 MB per file, all adjustable. Recycle bins, .git and node_modules are always skipped.
  • The SQL dialect is DuckDB — the same SQL you would write against any other connector.

Cross-source SQL

Join CSV Folder to the rest of your data

A folder of files is a set of SQL tables like any other, so one statement can join it to a database and an API at once. Each source runs only the part it can, streams the result back, and the join happens centrally — the sources never talk to each other and nothing is copied anywhere.

3 connections · 3 agents

CSV Folder Spreadsheet files
PostgreSQL Relational engine
Stripe Payments & billing

One statement

-- nothing copied, nothing merged, nothing scheduled
SELECT   c.region, COUNT(*) AS orders, SUM(i.amount_due) AS invoiced
FROM     csv_drops.fileset.data1  f
JOIN     pg_crm.public.customers2 c ON c.id = f.customer_id
JOIN     billing.stripe.invoices3 i ON i.customer = c.stripe_id
GROUP BY c.region
ORDER BY invoiced DESC;

The three parts are connection, schema and table — and the connection name is whatever you called it. Illustrative columns; your tables will be your tables. Read-only applies to every piece: SELECT, WITH and EXPLAIN only, with a ceiling on how much any one source may hand over for a single query. How federated queries work

Connection details

What CSV Folder needs

Folder
One or more roots — local disk or a network share typed as \\server\share (never a mapped drive letter; on Linux or a Mac, mounted first); subfolders included, include and exclude patterns supported
Schema
Sampled from the real files on first sync — delimiter, quote character, header row, encoding, date formats — then pinned
Encodings
UTF-8, UTF-16, Windows-1252 and Latin-1, detected per file
Money columns
A column that always holds decimals is stored as exact DECIMAL, never floating point
Limits
Up to 250,000 files, 16 folder levels deep, 512 MB per file — all adjustable
Credentials
None — there is no server; the agent reads the files in place
SQL dialect
DuckDB — standard SQL, nothing folder-specific to learn

There is no database server in this picture. The agent reads the .csv files where they already live, caches the rows in an encrypted DuckDB store on the same machine, and re-reads only files that actually changed — a folder of 50,000 files is not re-parsed because one new export landed. Nothing is uploaded to Query Streams; the only thing that ever leaves your network is the result of a query.

Recurring exports of the same report belong in one table, and that is the default. If the folder genuinely holds different CSVs — a customer list sitting beside an order dump — per-layout mode gives each distinct layout its own table, up to 25 of them.

FAQ

Questions about CSV Folder

Which tools can read CSV Folder data through Query Streams?

All of them, from one connection: Excel, Google Sheets, MCP, REST API, Airtable, Baserow, SeaTable, Smartsheet, Anvil, Power BI, scheduled alerts and reports. Connect the folder once and every surface reads the same read-only connection — there is no per-tool setup and no second copy of the data.

Do my files get uploaded to Query Streams?

No. The Network Agent reads the files in place and caches rows in an encrypted store on the same machine. The files themselves never leave your network — only the result rows of a query do, over a single outbound encrypted connection with no inbound firewall port.

Can Query Streams change, move or rename my files?

No. Files are opened strictly read-only and are never written, moved or renamed. Queries are enforced read-only at the point of execution — one statement at a time, SELECT and friends only.

What does Query Streams need to connect to CSV Folder?

A folder path the agent machine can see — no server, no credentials, no drivers to install. Folder: One or more roots — local disk or a network share typed as \\server\share (never a mapped drive letter; on Linux or a Mac, mounted first); subfolders included, include and exclude patterns supported. Schema: Sampled from the real files on first sync — delimiter, quote character, header row, encoding, date formats — then pinned. Encodings: UTF-8, UTF-16, Windows-1252 and Latin-1, detected per file. Money columns: A column that always holds decimals is stored as exact DECIMAL, never floating point.

Can I join a folder of files to a database in the same query?

Yes — that is a federated query. One statement can reference CSV Folder and your other connections at once, written as connection.schema.table. Each source runs only the part it can and streams the result back; the join happens centrally, so the sources never connect to each other and nothing is copied or scheduled. Read-only applies to every piece — SELECT, WITH and EXPLAIN only — and there is a ceiling on how much any one source may hand over for a single query. Federated queries are a plan feature; the federated queries page carries the current source and size limits.

Put CSV Folder where the work happens

Install the agent, point it at your folder, and pick a destination.

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Read-only Outbound only Credentials stay on the agent