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SQL CSV Chomper

SQL CSV Chomper

Mark Sawczuk

|
1 install
| (0) | Free
Chomp through CSV files with SQL! Powered by DuckDB with column filtering, inline editing, virtual scrolling, Save As, and an MCP server for Claude/Copilot.
Installation
Launch VS Code Quick Open (Ctrl+P), paste the following command, and press enter.
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More Info

SQL CSV Chomper

SQL tools for you. SQL tools for your LLM.

Stop staring at raw CSV text. Stop copy-pasting into Excel. Stop writing throwaway Python scripts just to peek at your data. SQL CSV Chomper turns VS Code into a fast, lightweight SQL workbench for your data files — powered by DuckDB WASM running entirely in your browser. No server, no database, no nonsense.

Open any CSV. Write SQL. Get results. Chomp chomp.

Open a CSV and click "Edit CSV" to launch the Chomper

Why?

Working with CSV files in VS Code has always been painful. Need to filter 500K rows? Join two CSVs? Edit a single value and save? Your options were Excel, a Python REPL, or a full database setup. None of those live inside your editor.

And if you're working with an AI assistant? Every CSV operation means another round-trip — "write me a script to filter this", "now save it back", "actually change that column name first". It's slow.

Chomper fixes both problems. You get a visual SQL IDE with filtering, editing, and sorting. Your AI gets an MCP server with direct SQL access to your files. Everyone chomps faster.

Features

Query 500K+ rows without breaking a sweat

Data loads in 10,000-row chunks with automatic pagination as you scroll. The status bar shows exactly where you are — no freezing, no waiting.

Full query interface with schema explorer, SQL editor, and results table

Excel-style column filtering

Click the filter icon on any column header to get a rich filter panel:

  • Value checkboxes with frequency bars and counts
  • Search within the value list (Select All respects your search)
  • Null statistics and distinct count
  • Active filters appear as chips above the table — click to remove

Filter panel showing value checkboxes with frequency counts

Date & time intelligence

Date columns get special treatment — histogram buckets by hour, day, week, month, or year. Click any bucket to instantly filter to that time range.

Date column filter with temporal histogram buckets

Edit cells inline and save back

Double-click any cell to edit in place. Changes update the in-memory database instantly. Hit Save to write back to disk, or Save As to export with custom delimiters, quoting, and formatting.

Inline cell editing with save and filter tokens

SQL intellisense

Full autocomplete for table names, column names (auto-quoted when they contain spaces), SQL keywords, and 60+ DuckDB built-in functions.

SQL autocomplete showing table and column suggestions

Scroll through massive files

Virtual scrolling keeps things smooth even with hundreds of thousands of rows. Load more data automatically as you scroll, or run a query to narrow things down.

Scrolling through a large filtered dataset

Column operations

Right-click any column header to rename, insert, or delete columns. Load multiple files and JOIN across them — the schema explorer shows every table with columns, types, unique counts, and null percentages.

Find & Replace

Search and replace across any column with case-sensitive and regex support. Live match count shows how many values will change before you commit.

Save As with options

Export your data exactly how you need it:

  • Delimiter: comma, tab, pipe, semicolon, or custom
  • Quoting: always, as needed, or never
  • Options: include/exclude header, add row numbers
  • Format: .csv, .tsv, .txt

MCP Server — Let your AI chomp too

SQL CSV Chomper includes a bundled MCP (Model Context Protocol) server so AI assistants can work with your CSV files directly. No more "write me a Python script to filter column X" — just let them query.

GitHub Copilot

The MCP server registers automatically in VS Code 1.99+. Copilot can load files, run queries, edit data, and push results into the visual editor.

Claude Code

Option 1 — From VS Code (easiest):

  1. Cmd+Shift+P (or Ctrl+Shift+P)
  2. Search "SQL CSV Chomper: Configure MCP for Claude CLI"
  3. Choose User (all projects) or Project (this workspace)
  4. Done — Claude can now chomp your CSVs

Option 2 — From the terminal:

# Find the extension's MCP server path
CHOMPER_MCP="$(find ~/.vscode/extensions -path '*/sql-csv-chomper-*/out/mcp/server.js' | head -1)"

# Add for all projects
claude mcp add sql-csv-tool --scope user -- node "$CHOMPER_MCP"

# Or add for just the current project
claude mcp add sql-csv-tool --scope project -- node "$CHOMPER_MCP"

Option 3 — Manual config (add to ~/.claude/settings.json or .claude/settings.json in your project):

{
  "mcpServers": {
    "sql-csv-tool": {
      "type": "stdio",
      "command": "node",
      "args": ["~/.vscode/extensions/marksawczuk.sql-csv-chomper-0.2.0/out/mcp/server.js"]
    }
  }
}

Note: The version number in the path (e.g. 0.2.0) will change with updates. Use the find command above or the VS Code command palette to get the correct path.

MCP tools available

Tool What it does
load_csv Load a CSV/TSV file as a named table
execute_sql Run any SQL query
list_tables List all loaded tables
list_columns Get column names and types
get_schema Full schema for all tables
update_rows Update rows matching a condition
insert_row Insert a new row
delete_rows Delete matching rows
save_table Export a table to CSV
set_editor_sql Push SQL into the editor
run_editor_query Set and run SQL in the editor

Keyboard shortcuts

Shortcut Action
Ctrl+Enter Run query
Shift+Alt+F Format SQL
Ctrl+H Toggle Find & Replace
Escape Close menus / cancel edit
Right-click cell Context menu with filter options
Right-click header Column operations

Supported files

Extension Format
.csv Comma-separated values
.tsv Tab-separated values
.tab Tab-delimited
.txt Text (auto-detected delimiter)
.jsonl JSON Lines

How it works

  • DuckDB WASM runs entirely in your browser — zero external dependencies
  • Files load into an in-memory DuckDB instance when opened
  • SQL executes at native speed against the in-memory database
  • Edits modify the in-memory table; Save writes back to disk
  • The MCP server runs a separate DuckDB instance for AI workflows

Requirements

  • VS Code 1.85+
  • Node.js (for the MCP server only)

License

MIT

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