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All directories
Curated opportunity · Startup directory

Lib Hunt

libhunt.com

Discover the most popular open-source projects, libraries, and tools in various programming languages, ranked by social media mentions and developer engagement.

PricingFree
Link typeConditional
Domain Rating62Domain Rating by Ahrefs
EvidenceDirectly verified
Why it made the cut

Our editorial take

A specialist repository-discovery destination. Include it when the public code repository is the product or an important part of it.

Pricing evidence: Reported by a public source list; confirm current pricing with the destination.

Link evidence: Mixed link attributes observed across 15 sampled external homepage links on 2026-07-14; behavior likely varies by placement or tier.

Best fit

Who should consider Lib Hunt?

Open-source libraries and repositories that developers compare within a programming ecosystem.

Submission path

How to submit to Lib Hunt

Use the verified submission destination linked above. Confirm the current eligibility rules, prepare a consistent product identity, and review any account or editorial requirements before sending your information.

Before you submit

What to verify

Submission rules can change between reviews. Check the live destination before investing time or paying a fee.

  • Confirm the destination still accepts your product type.
  • Review current pricing and editorial requirements.
  • Prepare a truthful description, logo, screenshots, and canonical URL.
Supporting evidence

Directory Score: 81/100

The score helps order already-curated opportunities. It does not decide what gets published.

  • Strong product fit
  • Active submission opportunity
  • Accessible submission process
25% product and audience fit20% listing visibility and permanence20% current submission activity15% cost and submission effort10% citation value10% domain authority

Confidence: 100%. The score does not guarantee acceptance, traffic, backlinks, or rankings.

Agentic-first directory data

Built for people. Structured for agents.

Use canonical machine-readable access to Lib Hunt's directory record: JSON for structured fields or concise LLM text for retrieval and analysis. These public representations mirror the visible data; access does not guarantee model ingestion or citation.