DataOps ClickHouse MCP server with query optimization and pipeline monitoring
DataOps ClickHouse MCP server with query optimization and pipeline monitoring
A DataOps-focused MCP server for ClickHouse with query optimization, pipeline latency analysis, and data quality monitoring.
clickhouse-dataops-mcp on PyPI is all you need. Most clients run it directly, so configuration is a few lines and a restart.
You will need 3 environment variables: CLICKHOUSE_HOST, CLICKHOUSE_PORT, CLICKHOUSE_DATABASE. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.
Among the database access options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. It is maintained by Aguantar; worth a glance at recent repository activity before you build anything load-bearing on it.
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{
"mcpServers": {
"clickhouse-dataops": {
"command": "uvx",
"args": ["clickhouse-dataops-mcp"],
"env": {
"CLICKHOUSE_HOST": "your-value",
"CLICKHOUSE_PORT": "your-value",
"CLICKHOUSE_DATABASE": "your-value"
}
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
| Variable | Description | Required |
|---|---|---|
| CLICKHOUSE_HOST | Endpoint or connection string the server talks to. | Optional |
| CLICKHOUSE_PORT | Configuration value read at startup. | Optional |
| CLICKHOUSE_DATABASE | Configuration value read at startup. | Optional |
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