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Check that npm and PyPI packages really exist before installing them

notary_check_packages
Read-onlyIdempotent

Use when the user or an agent is about to install or import npm or PyPI packages: before npm install or pip install, when adding lines to package.json or requirements.txt, or when a package name came from an AI answer, a tutorial or memory and may be invented. Looks each name up in the live registry and returns whether it exists, the latest version, whether a pinned version exists, weekly downloads, first and last publish dates, deprecation or yanked status, install-time scripts, whether the name is one or two typed characters from a well-known package, and real similar packages when the name does not exist. Example: {"packages":[{"ecosystem":"npm","name":"@anthropic/mcp-client"},{"ecosystem":"pypi","name":"requests","version":"2.32.3"}]}. Up to 10 packages per call; versions must be exact, not ranges. Not a malware or vulnerability scan: "ok" means it exists and nothing looked wrong.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "packages": "<packages>"
    },
    "name": "notary_check_packages"
  }
}

Input Schema

NameRequiredDescriptionDefault
packagesYes1 to 10 packages to look up.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.8/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare read-only, open-world, idempotent, non-destructive, and the description adds substantial context beyond them: it enumerates the returned fields (existence, latest version, pinned-version existence, downloads, publish dates, deprecation/yanked, install scripts, typosquat distance, similar names). It also discloses the 10-package cap and the exact-version-only constraint, and bounds the trust signal by saying 'ok' does not mean safe.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

It is front-loaded with the use case, then returns, then example, then constraints — a sensible order with no filler sentences. The main weakness is that it is delivered as one dense paragraph, so the example JSON and the limits are harder to scan than they would be as separate lines.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, and the description compensates by listing exactly what comes back and what 'ok' does and does not guarantee. Combined with the input constraints (max 10, exact versions) and the example call, an agent has everything needed to invoke it correctly and interpret the result.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so per-field meaning is already documented; the description still adds a full example payload and the rule that versions must be exact rather than ranges, plus the per-call limit. It does not add much about the ecosystem enum beyond what the schema states, so it sits just above the baseline rather than at the top.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: verify that npm and PyPI package names exist in the live registry before install. The title reinforces it and the scope (two ecosystems, existence + metadata) is unambiguous, so an agent can distinguish it from the sibling check tools (DNS, email domain, contrast, Supabase access) at a glance.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It names concrete trigger moments: before npm install or pip install, when editing package.json or requirements.txt, and when a name came from an AI answer, tutorial, or memory. It also gives an explicit exclusion — 'Not a malware or vulnerability scan' — which prevents the most likely mis-invocation, and clarifies what 'ok' means.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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