AI & MemoryMCP RegistryremoteB · 70

nlqdb — analytical memory for AI agents MCP server

Name: nlqdb — analytical memory for AI agents
Author: nlqdb.com

com.nlqdb · Updated 3mo ago

Analytical memory for AI agents: a real Postgres queried in plain English over MCP. One command.

At a glance

nlqdb — analytical memory for AI agents is an MCP server in the AI & Memory category. It is hosted remotely and connects over HTTP, and declares no required credentials. It scores B (70/100) on the MCP Skills Hub health score as of Oct 28, 2026.

Source 2

One-click install

VS Code VS Code Insiders Cursor

Opens your editor and pre-fills the config. Your editor will ask before adding it.

How to install nlqdb — analytical memory for AI agents in your AI client

Setup for Claude Code, Claude Desktop, Cursor, Codex, Windsurf, Cline and VS Code — copy-paste ready.

How to install nlqdb — analytical memory for AI agents in Claude CodeAnthropic's agentic CLI

Add the server

bash

claude mcp add --transport http nlqdb https://mcp.nlqdb.com/mcp

2
Verify it's connected
bash
```
claude mcp list
```
Sharing it with your team?
Add `--scope project` to write it to .mcp.json in the repository root, which you can commit (with the secrets left as environment variables).
Use it in a session
Ask Claude to use the tools this server exposes. It discovers them automatically.

How to install nlqdb — analytical memory for AI agents in Claude DesktopDesktop app (MCP config)

Open your MCP config
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json · Windows: %APPDATA%\Claude\claude_desktop_config.json

Add this server

json

{
  "mcpServers": {
    "nlqdb": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://mcp.nlqdb.com/mcp"
      ]
    }
  }
}

Why the wrapper?
This is a remote (HTTP) server and Claude Desktop only launches local processes, so mcp-remote proxies the connection. It will open a browser window if the server needs OAuth.
Restart Claude Desktop
The tools appear under the 🔌 menu once the app reloads.

How to install nlqdb — analytical memory for AI agents in CursorAI-first code editor

Create / edit .cursor/mcp.json in your project

json

{
  "mcpServers": {
    "nlqdb": {
      "url": "https://mcp.nlqdb.com/mcp"
    }
  }
}

Enable it
Cursor Settings → MCP → toggle the server on. Tools become available to the Composer/Agent.

How to install nlqdb — analytical memory for AI agents in Codex CLIOpenAI coding agent

Add to ~/.codex/config.toml

toml

[mcp_servers.nlqdb]
command = "npx"
args = ["-y", "mcp-remote", "https://mcp.nlqdb.com/mcp"]

Why the wrapper?
Codex runs MCP servers as local processes, so mcp-remote bridges this HTTP endpoint to stdio.
Run Codex
Codex loads MCP servers from config.toml on startup and exposes their tools to the agent.

How to install nlqdb — analytical memory for AI agents in WindsurfCodeium's agentic IDE

Edit ~/.codeium/windsurf/mcp_config.json

json

{
  "mcpServers": {
    "nlqdb": {
      "serverUrl": "https://mcp.nlqdb.com/mcp"
    }
  }
}

Reload
Windsurf → Cascade → refresh MCP servers. Cascade can now call the tools.

How to install nlqdb — analytical memory for AI agents in ClineVS Code autonomous agent

Open Cline → MCP Servers → Configure
Adds to cline_mcp_settings.json.

Add the server

json

{
  "mcpServers": {
    "nlqdb": {
      "type": "streamableHttp",
      "url": "https://mcp.nlqdb.com/mcp"
    }
  }
}

How to install nlqdb — analytical memory for AI agents in VS CodeCopilot / MCP support

Create .vscode/mcp.json

json

{
  "servers": {
    "nlqdb": {
      "type": "http",
      "url": "https://mcp.nlqdb.com/mcp"
    }
  }
}

Start it
VS Code shows a ▶ Start action above the server entry. Agent mode (Copilot Chat) can then use the tools.

What tools does nlqdb — analytical memory for AI agents expose?

This server requires credentials before it will list its tools, so we cannot enumerate them here. Connect it in your client to see what it offers.

What the code can do

This is a remote server — nothing is installed or run on your machine, so there is no local code to analyze. What it can reach is described above: your requests go to the provider's host.

Before you install

Signals gathered from the source repo and package registry — not a safety verdict.

What it can reach

Third-party hosted service — Your requests and any data in them are sent to mcp.nlqdb.com.
No local execution — Nothing is installed or run on your machine.

Last commit today — Actively maintained.
2 GitHub stars — Very little community usage so far.

Client compatibility

Claude Code: NativeClaude Desktop: Via mcp-remoteCursor: NativeCodex CLI: Via mcp-remoteWindsurf: NativeCline: NativeVS Code: Native

Health score

B · 70

Maintenance, adoption, transparency and packaging — not a safety audit. How this is calculated

Maintenance30%100%
Last commit 0 days ago.
Adoption20%14%
2 stars.
Transparency20%75%
3/4: ✓ public source repo, ✓ declared license, ✓ documentation, ✗ discoverable tool list.
Provenance15%75%
Links to its own repository; package linkage unverified.
Packaging15%75%
Remote endpoint; authentication requirements not declared.

Documentation

Full README

nlqdb — your autonomous DBA.

nlqdb attaches to the Postgres or Cloudflare D1 database you already run, proposes the changes it needs, applies the ones you approve, measures them, and reverts any that regress.

Why it exists: the mission — encapsulate the trial-and-error journey every company walks to a good database infrastructure.

Where it is going (`docs/END_GOAL.md`): paste a connection string — on nlqdb.com, with the CLI, through the SDK, or from your coding agent over MCP — and the first proposals arrive within minutes, each with its expected effect, cost and inverse. Apply is one click; nlqdb then measures p95 on the same queries and keeps the change or reverts it, never on your app's request path. That loop is being built (Roadmap); what is live today is the hosted product below.

No backend to build. You write HTML; each component asks for what it wants in plain English; nlqdb infers the schema, writes the SQL, runs it, and renders the result. There is no backend for you to build.

Two actions. That's the whole product:

Create a database — one word: a name (or a goal).
Talk to it in plain English.

html

<script src="https://elements.nlqdb.com/v1.js" type="module"></script>

<nlq-data
  goal="the 5 newest orders, with customer and item"
  api-key="pk_live_xxx"
  template="table"
  refresh="10s"
></nlq-data>

That's the entire backend for a live order list — no API to write, no schema to define, no JSON to parse. Engine choice (Postgres / Mongo / Redis / DuckDB / pgvector / …), schema inference, indexing, backups, and auto-migration between engines based on your real workload are background concerns you never have to see.

Status — early, open

nlqdb is early and built in the open, but fully public — no gate, no invite code. The marketing site, the /v1/ask pipeline, the <nlq-data> / <nlq-action> elements, the chat app, the TypeScript SDK, the hosted MCP server, and the nlq CLI are all live in some form (see the surface table below). Natural-language → SQL accuracy is still climbing toward our public bar (BIRD ≥ 0.65, Spider 2.0 ≥ 0.75 on the free model chain), so answers can be wrong — every response carries a confidence signal and the SQL it ran.

Use it

Connecting an agent over MCP? On Claude Code, one marketplace add wires the hosted server *and* both memory skills in a single step:

text

/plugin marketplace add nlqdb/nlqdb
/plugin install nlqdb-memory@nlqdb

Excerpt — the full document is on GitHub.

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