$ lurq verify lodahs
lodahs  ✗ do not install 0.0.1-security (latest) without review
  • name closely mimics "lodash" — possible typosquat
  • 1 critical/high advisory(ies) recorded against this package
risk flags: possible-typosquat-of:lodash, low-downloads, single-maintainer, has-known-advisory

$ lurq verify zod
zod  ✓ no supply-chain problems found in 4.6.4 (latest)
weekly dl:  209.2M   confidence: proven   advisories: 0

$ lurq compat next @auth/core next-auth
next + @auth/core + next-auth  conflict
peer-deps  next-auth needs peer @auth/core@0.34.3, but the stack uses @auth/core@0.41.3

Real output, not a mockup. Your agent gets the same answers over MCP.

Why your agent needs this

A model's knowledge of npm stops at its training cutoff. The registry doesn't.

• Invented and typosquatted names. Agents confidently install packages that don't exist, or that exist only because someone registered the misspelling.
• APIs that moved. Of the 38,752 packages lurq tracks, 2,725 shipped a new major version between May 1 and September 13, 2026. Code written from memory calls functions that were renamed or removed.
• Stacks that don't install together. Every package can be healthy on its own while the set fails on a peer or engine range. That usually surfaces at deploy.

lurq answers from evidence it can show: 47,238 packages scored, 4.2M versions tracked, 34,843 API surfaces extracted from shipped code, and 27M co-install pairs, refreshed daily from npm, GitHub, deps.dev and OSV. Every answer carries a dataAsOf timestamp.

Scope: the JavaScript/TypeScript ecosystem (npm).

Install

One command, once per machine. Nothing to install first:

npx lurqrun

The setup wizard:

1. Opens lurq in your browser. Sign in and the key comes back to the terminal by itself.
2. Detects every coding agent on the machine.
3. Writes a keyed remote MCP entry for each, in the shape that agent expects.
4. Installs standing instructions where the agent supports them, so it reaches for lurq instead of answering from memory.

Restart your agent afterward. The free plan includes 1,000 hosted calls a month and never asks for a card.

Works with: Claude Code · Cursor · Windsurf · VS Code / GitHub Copilot · OpenAI Codex CLI · Gemini CLI · Google Antigravity · Kiro

Check it worked: ask your agent to "add zod to this project". It should call lurq's verify before installing anything.

Claude Code plugin, no terminal needed:

/plugin marketplace add jadenryu/lurq
/plugin install lurq@lurq

One-click links for Cursor and VS Code are in the quickstart.

The package is published as lurqrun (the bare name was taken). The command is lurq:

npm install -g lurqrun
lurq --version

For AI agents

If you are an AI coding agent and your user asked you to set up lurq, follow these steps.

1. Run setup.

npx lurqrun setup

In your shell it does not prompt: it prints a one-time sign-in link and exits right away. Give the user that link. When they sign in on this computer, lurq stores a key and connects every detected coding agent by itself. Never invent a key.

2. Or configure non-interactively when the user already has a key from lurq.run/dashboard/keys, or on a cloud, SSH or CI machine, where a sign-in link on this computer can't work:

npx lurqrun setup --yes --no-open --api-key <key> --agent <id>

--agent all configures every detected agent. With --yes, the key can also come from LURQ_API_KEY.

Some checks need no key at all. npx lurqrun check-upgrade --upgrade <package>@<from>..<to> compares an upgrade against the names your code actually imports, locally.

3. Tell the user to restart the agent, then confirm lurq appears in its MCP tool list.

"lurq": { "type": "http", "url": "https://api.lurq.run/mcp", "headers": { "Authorization": "Bearer <key>" } }

"lurq": { "url": "https://api.lurq.run/mcp", "headers": { "Authorization": "Bearer <key>" } }

"lurq": { "serverUrl": "https://api.lurq.run/mcp", "headers": { "Authorization": "Bearer <key>" } }

"lurq": { "httpUrl": "https://api.lurq.run/mcp", "headers": { "Authorization": "Bearer <key>" } }

[mcp_servers.lurq]
url = "https://api.lurq.run/mcp"
http_headers = { Authorization = "Bearer <key>" }

When to call lurq

When lurq flags something, tell the user what it found and that it came from lurq. An unknown or UNVERIFIABLE result means lurq could not check. It never means the package is clean.

Machine-readable docs: lurq.run/llms.txt · lurq.run/docs/llms-full.txt

MCP tools

Fifteen tools. Responses are compact to save tokens, and package answers carry dataAsOf.

Before installing

Across a stack

Writing code

MCP servers

About lurq

Inputs, outputs and verdict definitions for each: MCP tools reference.

CLI

The same index, scriptable. Every read command takes --json.

# Before installing
lurq verify jsonwebtoken
lurq evaluate zod
lurq compare date-fns dayjs moment

# Stacks and projects
lurq compat next react react-dom
lurq audit .                               # every dependency and MCP server in the project

# APIs and upgrades
lurq usage zod --known 3.22.4              # what changed since the version you know
lurq upgrade-plan .                        # what's behind, and what each upgrade removes
lurq check-upgrade . --plan lurq-plan.json --exit-code

# Publishing your own package
lurq check-release                         # is the version you're about to publish honest?
lurq check-api --against origin/main       # does this break your API's callers?

# MCP servers
lurq mcp-scan                              # read the servers you have configured, record what changed

# Team policy
lurq policy pull policy.json               # keep the selection policy in a reviewed file
lurq policy push policy.json               # and apply it from CI (needs a policy:write key)

# Finding your way
lurq can "will this upgrade break my code" # which capability answers this?

Full reference: CLI docs.

Autopilot

lurq keeps a repository's dependencies current, and names the code an upgrade breaks before it merges.

The check reads the symbol-level API diff between versions and matches it against what your code actually references. It needs no tests.

blocking   a referenced symbol or deep import disappears,
           or require() of a now-ESM package breaks         → the code will throw
warning    a call's argument count no longer fits, a new type
           error, or a Node / peer version the repo lacks   → it may misbehave or not build
ok         nothing referenced is affected
unverified could not be established                         → never counted as safe

Three modes, and editing is opt-in. The workflow starts in comment: it plans, checks, writes the brief to the run summary, and changes nothing. fix opens a pull request containing only what the package itself proves — renamed call sites, and the range bump in every manifest — so it needs no Anthropic credential, and it is what a newly armed repo gets. pr is fix plus the agent, for the changes a rule cannot make. Step 4 above is the only one that needs a model, so only pr does.

The dashboard setting governs repos that already installed the workflow: each run reads the mode from the plan response rather than from the committed file.

Cadence follows scope — weekly for the scopes that track breakage, since majors arrive slowly enough that a daily run mostly reports nothing new; daily for a repo set to advisories-only, because weekly can mean seven days sitting on a known CVE.

Trust model. lurq's GitHub App holds Contents: read-only and Actions: write. It can read your manifests and start the workflow you committed — it cannot write a byte to your repository, change this file, or set a repository variable. Every write is made by the workflow itself using your own ephemeral GITHUB_TOKEN, bounded by the permissions: block in the file you control. The agent's allowlist is Read,Edit,Write,Bash(<pkg-manager>:*), so it edits files but never touches version control. Removing it is git rm .github/workflows/lurq-upgrade.yml.

What leaves your machine

Package names and versions, never your source code. audit receives the inventory your agent reads locally, check-upgrade matches symbols against your code on your own runner, and outcomes report names and counts only.

lurq mcp-scan is the one exception worth knowing: by default it records what your MCP servers expose (tool names, descriptions and parameters, with secrets redacted) to your account, so it can tell you what changed. --no-upload keeps the scan on your machine.

Where the evidence comes from

Readable: npm, GitHub, deps.dev and OSV, re-synced daily. Downloads, release cadence, maintenance, advisories, deprecations, license and bundle cost.

Executed: an isolated sandbox installs and imports package versions and records the results in a compatibility matrix. compat reads those edges alongside declared peer and engine ranges, which is why lurq can say whether a whole stack holds together.

Ranking is deterministic and public. No model sits in the scoring path:

health    = maintenance 0.35 · adoption 0.30 · reliability 0.25 · efficiency 0.10
quality   = types · tests · docs · changelog · dep count · license · provenance
composite = blend at a single tunable λ (default 0.35)

Every weight lives in src/scoring/weights.ts and prints with lurq weights.

Plans

Past the limit, calls slow to 20 a day rather than stopping. The CLI run against your own database is never metered. Details: pricing.

lurq uninstall                  # MCP entries, agent instructions, the stored key
lurq uninstall --agent cursor   # just one agent
npm uninstall -g lurqrun        # then remove the `lurq` command

Contact

Inquiries, partnerships or proposals: jadenryu@lurq.run

License

MIT