Nlqueries vs DBHub Analytics — MCP Server Comparison | AllMCPs
Nlqueries vs DBHub Analytics
A side-by-side look at the Nlqueries and DBHub Analytics MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Nlqueries for databases work as a local process; choose DBHub Analytics for databases as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose Nlqueries when
You need dedicated capabilities in the Databases domain.
You prefer a local stdio subprocess transport.
You have the keys it needs: ANTHROPIC_API_KEY, OPENAI_API_KEY, QDRANT_API_KEY, NLQ_MCP_STATIC_TOKEN.
No tool names declared yet. Check the project README from the listing page.
DBHub Analytics tools 2
execute_sqlExecute SQL queries with read-only enforcement and row limiting
search_objectsBrowse catalogs, schemas, tables, columns, indexes, and routines
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
Nlqueries is categorized under Databases and uses a local stdio subprocess. DBHub Analytics belongs to Databases and uses a local stdio subprocess. Pick Nlqueries for databases work and DBHub Analytics for databases.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.
Nlqueries has no declared pricing — check the project's own site. DBHub Analytics has no declared pricing — check the project's own site. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add nlqueries-nlqueries and dbhub-analytics as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Nlqueries has a quality signal of 49/100 (Fair) with 1 views, 0 installs and 4 GitHub stars. DBHub Analytics has 48/100 (Fair) with 2 views, 0 installs and 0 GitHub stars.