aiQueryLab

AI-collaborative DB IDE for VSCode. Execute queries from .sql files, view results as tables or charts, and let an AI (via MCP) drive the same panel — read queries, edit queries, run queries, push results back.

Status

Scaffold. MySQL + ClickHouse adapters wired. MCP server (HTTP + bearer) exposes list_connections, execute_query, get_result, inject_result, pin_result, list_results. Svelte webview with table + ECharts chart host. Chart config = plain JS file next to the .sql (queries/foo.sql → queries/foo.chart.js).

Related MCP server: MySQL MCP Server

Roadmap

• v0: MySQL + ClickHouse, execute-under-cursor, results panel, MCP wiring

• v1: connection editor UI, richer chart presets

• v2: Redis, Iceberg, Elasticsearch adapters

• v3: multi-tab result slots, streaming large results

Install

One-liner (installs into detected editor CLI: code / cursor / code-insiders / codium):

curl -sSL https://raw.githubusercontent.com/gr4c2-2000/aiQueryLab/main/install.sh | bash

Or from a local clone:

git clone https://github.com/gr4c2-2000/aiQueryLab.git
cd aiQueryLab
AIQL_LOCAL=1 ./install.sh

Install (dev)

npm install
cd webview && npm install && cd ..
npm run build

Then open the folder in VSCode and press F5 to launch the Extension Development Host.

Configuration

• .aiql/connections.json — connection specs (checked into repo, no passwords)

• Passwords — stored in VSCode SecretStorage per connection

• .aiql/config.example.json — full config schema (also exposed via VSCode settings under aiql.*)

MCP

After activation, run aiQueryLab: Copy MCP Config to get a snippet like:

{
  "mcpServers": {
    "aiquerylab": {
      "url": "http://127.0.0.1:53827/mcp",
      "headers": { "Authorization": "Bearer <token>" }
    }
  }
}

Paste into your MCP client (Claude Code, etc). Available tools:

Charts

Convention: queries/foo.sql → optional queries/foo.chart.js.

// queries/foo.chart.js
function render(data, ctx) {
  const { records } = data;
  ctx.setOption({
    tooltip: { trigger: 'axis' },
    xAxis: { type: 'category', data: records.map(r => r.day) },
    yAxis: { type: 'value' },
    series: [{ type: 'bar', data: records.map(r => r.count) }],
  });
}

data = { columns: string[], rows: unknown[][], records: Record<string, unknown>[] }. ctx = { echarts, container, setOption }.

Storage

Results persist to .aiql/cache/results/<resultId>/{data.ndjson,meta.json}. Sliding-window LRU keeps total under storage.results.maxSizeMb (default 500). Set storage.results.mode = "unlimited" to disable eviction. pin_result protects specific results.

Logs write to .aiql/logs/aiql-YYYY-MM-DD.log, JSON-lines, capped by retentionDays and maxSizeMb.

License

Apache 2.0. See LICENSE.