package-intel-mcp

Package Downloads

package_downloads

Read-onlyIdempotent

Retrieve recent download counts for npm, PyPI, or Cargo packages to assess how widely used and battle-tested a dependency is.

Instructions

Get popularity/download statistics for a package (recent download counts). Useful for judging how widely used and battle-tested a dependency is. Ecosystems: npm, pypi, cargo.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`name`	Yes	Exact package name as published in that registry, e.g. express for npm, requests for pypi, serde for cargo.
`ecosystem`	Yes	Package registry to look in. One of: npm, pypi, cargo.

Output Schema

TableJSON Schema

Name	Required	Description
`ecosystem`	No
`last_month`	No
`provenance`	No	Where this answer came from. served_at is when Datakoot answered (UTC); upstream lists the official sources consulted. Datakoot may serve a briefly cached copy, so the source's own observation can be older than served_at.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.1.0Oct 15, 2026

TDQS

A3.8/5.0

Behavior3/5

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

Annotations already declare readOnly, idempotent, open-world and non-destructive, so the safety profile is covered. The description adds only the notion of 'recent' download counts, without specifying the time window, data source, or rate limits — modest added value beyond structured data.

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

Conciseness5/5

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

Three short, front-loaded sentences with no filler; the purpose comes first and the ecosystem scope is confined to a single closing clause.

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

Completeness4/5

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

With an output schema present, return-value documentation is not required, and the description covers purpose, scope and the ecosystem boundary. It is slightly thin on the 'recent' semantics, which matters for interpreting the returned numbers.

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

Parameters3/5

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

Schema description coverage is 100% and both parameters are documented in the schema with examples and an enum, so the description need not compensate. It confirms the three supported ecosystems but adds no naming or format guidance beyond the schema.

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

Purpose4/5

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

States a specific verb and resource: retrieve popularity/download statistics for a package, with the qualifier 'recent download counts'. It implies separation from package_info/package_versions/package_health but never names or contrasts with any sibling, so differentiation is left to inference.

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

Usage Guidelines4/5

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

'Useful for judging how widely used and battle-tested a dependency is' gives a clear decision context for choosing this tool, and the ecosystems list scopes it. It stops short of saying when to prefer it over package_health or package_info, or any exclusions.

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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