Programmatic usage
Start the hypequery MCP server from a Node process.
Use createMCPServer when you want to start the MCP server from your own Node process instead of using the CLI.
import { createMCPServer } from '@hypequery/mcp';
import { createDatasetClient } from '@hypequery/datasets';
import { createQueryBuilder } from '@hypequery/clickhouse';
import { datasets } from './datasets/index.js';
const db = createQueryBuilder({
url: process.env.CLICKHOUSE_URL!,
username: process.env.CLICKHOUSE_USERNAME!,
password: process.env.CLICKHOUSE_PASSWORD!,
database: process.env.CLICKHOUSE_DATABASE!,
});
const analytics = createDatasetClient({ queryBuilder: db });
const server = await createMCPServer({
datasets,
analytics,
name: 'analytics-mcp',
version: '1.0.0',
});
// The server is now running over stdio.createMCPServer returns the server instance after calling start(). The stdio transport is intended for MCP clients that launch and manage the process.
Tenant-scoped servers
If registered datasets have tenantKey, pass a trusted tenantId when creating the MCP server.
const server = await createMCPServer({
datasets,
analytics,
tenantId: 'tenant_123',
});The server forwards that value as dataset runtime tenant context for query_dataset and query_metric.
Stop the server
If your application owns the lifecycle, call stop().
await server.stop();Config shape
The programmatic API accepts the same core inputs as the CLI config, plus optional server metadata and tenant scope.
type MCPServerConfig = {
datasets: Record<string, Record<string, unknown>>;
analytics: DatasetClient;
name?: string;
version?: string;
tenantId?: string;
includeSql?: boolean;
};Set includeSql: true only in trusted debugging contexts. Query tools redact generated SQL by default.