aiQueryLab MCP Server
Enables AI to execute SQL queries against MySQL and ClickHouse connections, retrieve and manage results, and inject them into the aiQueryLab VSCode IDE.
README
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).
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
SecretStorageper connection .aiql/config.example.json— full config schema (also exposed via VSCode settings underaiql.*)
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:
| Tool | Purpose |
|---|---|
list_connections |
enumerate configured connections |
execute_query |
run a single statement, get resultId + preview |
get_result |
paginated read of stored result rows |
inject_result |
push a stored result to the open results panel (optional slot) |
pin_result |
mark result immune to eviction |
list_results |
enumerate stored results (metadata) |
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.
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