package-intel-mcp

Package Dependencies

package_dependencies

Read-onlyIdempotent

List direct dependencies for a specified npm, PyPI, or cargo version before adding it, helping agents see what a library pulls in.

Instructions

List the direct dependencies of a specific package version (defaults to latest), via deps.dev. Lets an agent understand what a package pulls in before adding it. Ecosystems: npm, pypi, cargo.

Input Schema

TableJSON Schema

Name	Required	Description
`name`	Yes	Exact package name as published in that registry, e.g. express for npm, requests for pypi, serde for cargo.
`version`	No	Optional; defaults to the latest/default version
`ecosystem`	Yes	Package registry to look in. One of: npm, pypi, cargo.

Output Schema

TableJSON Schema

Name	Required	Description
`name`	No
`source`	No
`version`	No
`ecosystem`	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.
`direct_dependencies`	No
`dev_dependency_count`	No
`build_dependency_count`	No
`direct_dependency_count`	No
`required_dependency_count`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.1.0Oct 15, 2026

TDQS

A4/5.0

Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, and the description adds genuinely new behavioral facts: results come from deps.dev, the scope is direct (not transitive) dependencies, and version defaults to latest. It omits rate limits and result shape, but the output schema covers the latter.

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?

Three short sentences, front-loaded with the core action before the rationale and supported ecosystems. Slightly redundant in re-listing 'npm, pypi, cargo' when the schema already enumerates them.

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?

For a simple read-only lookup with rich annotations, full schema coverage, and an output schema, the description supplies everything needed to select and invoke it correctly: source, scope, default behavior, and supported ecosystems.

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%, with clear per-parameter descriptions and an enum for ecosystem, so the baseline is 3. The description only restates the version default and lists the ecosystems, adding nothing the schema does not already provide.

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?

Specific verb (List) plus precise resource and scope: direct dependencies of a specific package version, sourced from deps.dev. The 'direct' qualifier separates it in spirit from a transitive-dependency or package_info sibling, though no sibling is named explicitly.

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?

Gives a concrete use context – understanding what a package pulls in before adding it – which tells the agent when this tool is relevant. It stops short of naming alternatives (package_info, package_health) or stating when not to use it.

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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