What is Package Documentation Fetcher?

46/100
Trust Score (D)
⚠️ Use Caution

Package Documentation Fetcher is a coding that Fetches up-to-date library information from multiple package registries and documentation sources.. It has a Nerq Trust Score of 46/100 (D). 15 GitHub stars. Published by https://github.com/cdugo/package-documentation-mcp. Last analyzed November 2026.

Why This Score

Trust & Safety Overview

46
TRUST SCORE
D
GRADE
15
STARS
0
DOWNLOADS

What Package Documentation Fetcher Does

Package Documentation Fetcher is a mcp_server in the coding category. Fetches up-to-date library information from multiple package registries and documentation sources.. It is published by https://github.com/cdugo/package-documentation-mcp and has no specified license. With 15 GitHub stars and 0 downloads, it has a small community of users and contributors.

Who Should Use Package Documentation Fetcher

Package Documentation Fetcher is recommended only for experimental use. Consider alternatives with higher trust scores for production systems.

Details

Authorhttps://github.com/cdugo/package-documentation-mcp
Categorycoding
LicenseNot specified
Typemcp_server
SourceView on GitHub
Security Score0/100
Activity Score0/100

How to Get Started

Check the trust score before installing:

curl nerq.ai/v1/preflight?target=package-documentation-fetcher

Setup guide · Full safety report · Production review · Is it safe?

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Frequently Asked Questions

What is Package Documentation Fetcher used for?
Package Documentation Fetcher is a coding tool. Fetches up-to-date library information from multiple package registries and documentation sources..
Is Package Documentation Fetcher free?
License: Check project page. Package Documentation Fetcher has 15 GitHub stars.
Is Package Documentation Fetcher safe?
Package Documentation Fetcher has a Nerq Trust Score of 46/100 (D). Evaluate carefully.
What are alternatives to Package Documentation Fetcher?
Top alternatives: AutoGPT, ollama, langchain. See full comparison.

Last updated November 2026. Trust scores based on automated analysis of public data.

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