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Nlqdb MCP Server

by Nlqdb
Developer ToolsLow Risk10.0MCP RegistryRemote
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Analytical memory for AI agents: a real Postgres queried in plain English over MCP. One command.

About

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

Remote endpoints: streamable-http: https://mcp.nlqdb.com/mcp

Security Report

10.0
Low Risk10.0Low Risk

Valid MCP server (1 strong, 1 medium validity signals). No known CVEs in dependencies. Imported from the Official MCP Registry. Trust signals: 3 highly-trusted packages.

Endpoint verified · Requires authentication · 1 issue found

Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.

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file_system

Check that this permission is expected for this type of plugin.

HTTP Network Access

Connects to external APIs or services over the internet.

How to Connect

Remote Plugin

No local installation needed. Your AI client connects to the remote endpoint directly.

Add this to your MCP configuration to connect:

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

Documentation

View on GitHub

From the project's GitHub README.

nlqdb — analytical memory for AI agents

Memory your agent can query, not just recall — a real database it reaches over MCP.

Connect nlqdb to Claude, Cursor, Codex, or any MCP host. Your agent writes typed rows as it learns, then asks questions in plain English — GROUP BY, JOIN, aggregate over what it remembered. A vector store returns the top-k similar chunks; nlqdb runs the query that a similarity index structurally can't. The LLM never emits SQL: it returns a typed plan, our compiler emits the parameterised statement, and you see the exact SQL every time.

It's also a natural-language database for any app. 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:

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

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

On any other MCP host, give your agent memory with one browser-OAuth approval; headless hosts skip the browser with npx -y @nlqdb/mcp (0.1.1) and an sk_mcp_* MCP key (MCP setup). @nlqdb/sdk (0.3.0) and @nlqdb/mcp (0.1.1) are both published and importable from npm.

The 60-second walkthrough — plain HTML, CLI, and ten framework wrappers — lives at docs.nlqdb.com. Start with the HTML tutorial or the CLI tutorial.

You don't generate an API key separately: describe your database at nlqdb.com, and the chat hands you a <nlq-data> snippet with the key already inlined.

Examples

examples/ — minimal scaffolds in plain HTML, Next.js, Nuxt, SvelteKit, Astro, plus a CLI-only walkthrough. Each is the smallest valid integration around one <nlq-data> element or one CLI session.

What makes it different

Four things every release has to move, none allowed to regress (GLOBAL-025):

  • Engine quality — natural-language → SQL accuracy (measured continuously on BIRD + Spider 2.0 + an internal eval), plus the multi-engine layer that moves your data to the right engine for your workload.
  • Onboarding — landing to first answer in under a minute, no card, no config.
  • UX — see the diff before any write, see the SQL behind every answer, and on low confidence get a one-click clarify — a guided turn, never a dead-end, and never a silent guess.
  • Performance — sub-400 ms cached, sub-1.5 s cold.

The bet: get this right on free, open models and it only gets better on frontier ones — the scaffolding compounds with whatever model is underneath.

Models & plans

  • Free forever on the built-in open-model chain — queries, embeds, and the elements, no card required.
  • Bring your own LLM key (Anthropic / OpenAI / Gemini / Grok / OpenRouter) on any tier, at no markup.
  • Hosted premium models on paid plans, when you'd rather not manage a key of your own.
  • Self-host the source — the engine, CLI, MCP server, and SDKs are source-available under FSL-1.1-ALv2: free to self-host for any non-competing use, bring your own LLM key, no per-call fees. The license auto-converts to Apache 2.0 two years after each release.

The hosted-premium model lane went live 2026-08-14. The full model strategy is in GLOBAL-026.

Surfaces at a glance

SurfaceStatusWhere
HTTP API (POST /v1/ask, POST /v1/run)✓ shippedapps/api/src/ask/**
<nlq-data> + <nlq-action> elements✓ shipped (v0.1)packages/elements/**
@nlqdb/sdk (TypeScript)✓ shipped (incl. runSql + cross-tenant grant verbs) — installable from npm (0.3.0)packages/sdk/**
Framework wrappers (React / Next / Vue / Nuxt / Svelte / SvelteKit / Astro / Solid + Swift)~ built + CI-tested; npm / SPM publish pendingpackages/{react,next,…}/**
Chat app nlqdb.com/app✓ shippedapps/web/**
Hosted MCP server mcp.nlqdb.com/mcp✓ shipped (host auto-detect pending)apps/mcp/**, packages/mcp/**
Local stdio MCP server @nlqdb/mcp✓ shipped (0.1.1) — npx -y @nlqdb/mcp with an sk_mcp_* keypackages/mcp/**
Droppable agent-memory artifacts (AGENTS.md · Claude Code skill + plugin · Cursor rules · Codex config)✓ shipped — /plugin marketplace add nlqdb/nlqdb installs the server + skills in one stepapps/web/public/agent-artifacts/**
nlq CLI (Go)✓ shipped (core verbs; device-login pending)cli/**

Full integration matrix in docs/progress.md.

Packages on npm

Published to the public npm registry with build provenance (SK-CIPERM-003). Version badges are live from npm; the table itself is generated from the workspace by scripts/sync-readme-packages.mjs, so it lists exactly the packages that are un-gated ("private" removed) and nothing that isn't.

PackageVersionWhat it isSource
@nlqdb/cli@nlqdb/cliShim that installs the nlq CLI binary for the host platform.packages/cli-shim
@nlqdb/mcp@nlqdb/mcpAnalytical-memory MCP server for nlqdb — a real database your AI agent can GROUP BY / JOIN / aggregate over in natural language, not just recall.packages/mcp
@nlqdb/sdk@nlqdb/sdkTyped HTTP client for the nlqdb /v1 API — works in browsers, Node, Bun, Workers.packages/sdk

Roadmap

The two sections below are the live focus; the numbered phases after them are the engine roadmap. Canonical plan + exit gates: docs/phase-plan.md. Legend: ✓ shipped · ~ in progress · ◯ planned.

This roadmap is yours to shape. Want something added, reprioritised, or dropped? Open a PR editing this section (and docs/phase-plan.md if it's engine-facing), or open an issue to float it first. Say why now — which of the four north-star pillars (engine quality, onboarding, UX, performance) it moves. New to the codebase? Point your coding agent at this repo and paste:

Read README.md and docs/phase-plan.md, then propose a roadmap change:
add/change "<your idea>" under the right section in one line, with a
"why now" naming which north-star pillar it moves. Open a PR with just
that edit — no code.

Setup, branch naming, and the CLA are in CONTRIBUTING.md.

Now — analytical agent memory (the wedge)

Memory your agent can GROUP BY: real Postgres tables per memory type, plain-English analytics over what it remembered — not top-k recall.

  • agent_memory_v1 preset — entities / facts / episodes, one command, live for every account
  • nlqdb_remember — deterministic write path (MCP tool + API + SDK + CLI)
  • nlqdb_read — read-only MCP tool a host can mark "always allow", so an agent queries memory with no prompt per call (writes stay on nlqdb_query)
  • ✓ Per-agent / per-end-user / per-thread isolation — hard RLS gates, fail-closed
  • ~ TTL retention — sweep built; cron wiring pending
  • /agents landing + honest competitor capability matrix
  • ✓ Claude Code plugin — /plugin marketplace add nlqdb/nlqdb installs the server + both memory skills in one step
  • ~ Dogfood gate — nlqdb's own ops running on nlqdb memory through the public MCP surface; the public launch fires when its five criteria are green
  • ✓ Public memory dashboard on /agents — live, aggregates-only block with an as-of date
  • ◯ One-click repo→memory import (paste a GitHub URL)
  • ◯ Goal packs — per-niche memory recipes (support-bot resolution ledger, research-agent source ledger, …)

Next — the expert-knowledge marketplace ("Become AI")

Non-technical professionals turn their expertise into structured, queryable knowledge that AI agents pay to use. Decisions locked, built in parallel with the wedge (docs/features/expert-knowledge-platform/).

  • ◯ Interview authoring — answer questions about your craft, get queryable rows (pilot: language tutor)
  • ✓ Cross-tenant read grants — mint/list/revoke control plane + live fail-closed granted read on /v1/ask (schema-only plan, rows-only egress, exactly-once per-query metering proven at the route boundary); revoke-in-flight bound measured against live Postgres
  • ◯ One catalog — free packs + paid expert knowledge DBs
  • ~ Trust hardening — buyer queries schema-only end-to-end: knowledge-DB asks skip narration by default and the granted cross-tenant read is un-narrated (returned rows never reach an LLM); no-training interview-provider pin pending

Phase 0 — Foundations ✓

Worker skeleton · KV + D1 + R2 bindings · Neon adapter + OTel · LLM router (free chain) · Better Auth (GitHub + Google + magic link) · /v1/ask end-to-end · events queue + drain · Stripe webhook · CI/CD + PR preview environments.

Phase 1 — On-ramp

A stranger lands on nlqdb.com, creates a DB in plain English, embeds it, and shares the link — in under 60 seconds, no card, no config.

  • ✓ Marketing site (Astro, live at nlqdb.com)
  • <nlq-data> + <nlq-action> elements (v0.1)
  • ✓ Sign-in — magic link + GitHub + Google
  • ✓ Chat surface — streaming three-part response (answer / data / trace), anonymous mode
  • ✓ Anonymous mode — 72h token, adopted onto your account on sign-in
  • ✓ Hosted db.create pipeline (table-card embeddings stubbed pending the pgvector slice)
  • ✓ API keys dashboard (/app/keys)
  • ◯ Hello-world tutorial polish

Phase 1.5 — Trust + telemetry

  • ✓ Diff preview on writes + visible SQL trace on every response
  • ✓ Demand-signal telemetry on every "not yet" path
  • ◯ Confidence floor (clarify-on-low-confidence — a guided turn, not a dead-end) — lands with quality-eval

Phase 2 — Distribution (agent + developer surfaces)

  • ✓ Hosted MCP server (mcp.nlqdb.com/mcp) — host auto-detect pending; local stdio @nlqdb/mcp@0.1.1 is on npm, so npx -y @nlqdb/mcp with an sk_mcp_* key is a headless route in with no browser consent step (/agents now carries it; the per-host install panel is still OAuth-only). On Claude Code, /plugin marketplace add nlqdb/nlqdb installs the server + both memory skills in one step
  • ✓ CLI nlq (Go) — core verbs + raw-SQL escape hatch; device-login + chat REPL pending
  • @nlqdb/sdk — basic methods + runSql + cross-tenant grant verbs; published and importable from the registry (0.3.0)
  • ~ Framework wrappers + native Swift package — built + CI-tested; npm / SPM publish pending
  • ✓ Quality-eval harness (BIRD + Spider 2.0, manual on-demand) — the free-vs-frontier accuracy delta is the headline KPI
  • ~ Bring-your-own-LLM dispatch — HTTP lane live; remaining surfaces in progress
  • ◯ CSV upload in chat
  • ~ Docs-site reference completeness — SDK + framework-wrapper guides, an enumerable error-code reference, and a build-time /llms.txt for agents now live; tutorial polish remains
  • ◯ Custom domains for embeds

Phase 3 — Multi-engine engine (the moat)

  • ◯ Workload analyzer → migration orchestrator
  • ◯ ClickHouse / DuckDB / Redis as additional engines
  • ◯ Dual-read verification
  • ✓ Hosted-premium model lane (demand-gated) — live 2026-08-14 (PREMIUM_METER_LIVE flipped)

Phase 4 — Beyond v1

  • ~ Bring-your-own Postgres / ClickHouse — connect path live end-to-end (POST /v1/db/connect + web UI, CLI, SDK, query dispatch); prod-gated on the BYO_SECRET_KEK secret. Supabase adds one-click OAuth connect over the read-only Management-API (no DSN to paste); prod-gated on the SUPABASE_OAUTH_CLIENT_ID / _SECRET secrets, with a graceful fall-back to paste when unset
  • ◯ SSO (SAML / OIDC), audit-log export, per-org quotas
  • ◯ EU data residency, VPC peering, SOC 2

Develop locally

git clone git@github.com:nlqdb/nlqdb.git && cd nlqdb
scripts/bootstrap-dev.sh   # installs everything, pulls Ollama models, seeds .envrc
scripts/login-cloud.sh     # signs you into cloud providers that have a CLI flow

bootstrap-dev.sh stands up the whole toolchain in one shot — Bun, Node 20+, Go 1.25+, uv; Biome / gofumpt / golangci-lint / ruff; lefthook git hooks; the cloud CLIs (wrangler, flyctl, stripe, gh); a local Ollama so the LLM router works offline; and a .envrc with self-generated dev secrets. Details in docs/history/infrastructure-setup.md §8.

Day-to-day:

bun run fix          # biome format + lint --write (most issues)
bun run check:all    # biome + golangci-lint + ruff (what CI runs)
bun run hooks:run    # run pre-commit hooks against staged files

End-to-end tests (manual trigger)

E2E coverage is persona-driven and manually triggered so cost stays inside the free-tier envelope — one workflow_dispatch workflow per surface:

gh workflow run e2e-opencheck.yml             # web — live LLM, Neon branch, Workers preview
gh workflow run e2e-cli.yml                   # Go testscript, hermetic
gh workflow run e2e-sdk.yml                   # vitest + cassettes, hermetic
gh workflow run e2e-mcp.yml                   # InMemoryTransport protocol tests, hermetic
gh workflow run e2e-examples.yml              # Playwright across HTML/Next/Astro/Nuxt/SvelteKit
gh workflow run e2e-examples.yml -f live=true # + staging for the curl + CLI shell smokes

Run the hermetic surfaces locally without GitHub:

( cd tests/e2e/cli && go test ./... )
( cd tests/e2e/sdk && bun install && bun run test )
( cd tests/e2e/mcp && bun install && bun run test )
( cd tests/e2e/examples && bun install && bun run install:browsers && bun run test )

Only execution is manual: tests/e2e/{sdk,mcp,examples} live outside the root workspace, so CI's typecheck-e2e job tscs them on every PR — the free backstop against a suite that compiles today and rots before the next dispatch.

Conventions, persona mapping, and cassette governance are in docs/features/e2e-coverage/FEATURE.md.

Docs & reference

Community & legal

  • CONTRIBUTING.md — dev setup, branch naming, commits, CLA flow.
  • CODE_OF_CONDUCT.md — Contributor Covenant 2.1. Reports to conduct@nlqdb.com.
  • SECURITY.md — vulnerability disclosure (security@nlqdb.com). 90-day fix target.
  • SUPPORT.md — where to ask questions and what we don't (yet) offer.
  • CLA.md — Contributor License Agreement, signed once via the bot on your first PR.
  • TRADEMARKS.md — what you can and can't do with the nlqdb name and logo.
  • SUBPROCESSORS.md — third-party services that may process personal data on our behalf.
  • IMPRESSUM.md — Swiss UWG-mandated operator disclosures.
  • Privacy policy and terms of service: nlqdb.com/privacy · nlqdb.com/terms.

License

FSL-1.1-ALv2 — Functional Source License, Apache 2.0 future license. Source-available for any non-competing use; auto-converts to Apache 2.0 two years after each release. (Pattern used by Sentry, Convex, and others.)

nlqdb™ is an unregistered trademark of the project's licensor. See TRADEMARKS.md for usage guidelines.

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