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ayhammouda

python-docs-mcp-server

lookup_package_docs

Read-onlyIdempotent

Retrieve official documentation, homepage, and source code URLs for any PyPI package by querying its metadata.

Instructions

Look up package-declared docs/homepage/source URLs via official PyPI metadata.

This is not generic web search: it only queries PyPI's JSON API and returns official PyPI metadata plus package-declared project URLs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
packageYesPyPI package/project name

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
packageYesCanonical package name returned by PyPI when available
versionYesLatest version reported by PyPI metadata
summaryNoPackage summary from PyPI metadata
metadata_sourceYesOfficial PyPI JSON API URL used for lookup
trust_boundaryNoIndicates results are limited to PyPI/project-declared metadatapypi-declared-metadata
sourcesNoPackage-declared PyPI, documentation, homepage, and source URLs
noteNoControlled-scope note, for example skipped labels or not-found details
Behavior3/5

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

Annotations already declare the tool as read-only and idempotent. The description adds context about querying PyPI's JSON API, which is consistent. No contradictions, but the added behavioral context is minimal.

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?

The description is very concise, with two sentences that are front-loaded: the first gives the core purpose, and the second clarifies scope. No unnecessary words or redundancy.

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?

Given the simple input (one parameter), comprehensive annotations, and existence of an output schema, the description is complete. It explains the tool's scope and limitations adequately for an agent to use it correctly.

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?

The input schema has 100% coverage for the single parameter 'package', with a description already present. The tool description does not add additional meaning or format details for the parameter beyond the schema, so it meets the baseline.

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?

The description clearly states it looks up package-declared docs/homepage/source URLs via PyPI metadata. It verbs are specific and the resource is well-defined. However, it does not explicitly differentiate from sibling tools like get_docs or search_docs, which may have overlapping functionality.

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

Usage Guidelines3/5

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

The description provides some usage guidance by contrasting with generic web search, indicating when not to use it. However, it does not explicitly state when to prefer this tool over its siblings, leaving some ambiguity for the agent.

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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