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When to use metawarc vs pywb vs warcio vs CDX

Evaluators often ask which tool to reach for. Short answer: metawarc is an operational index and analysis layer over local WARC collections. Source payloads stay in the original archives. Use other tools when you want their specialized strengths.

NeedPrefer
Index, query, extract metadata, and analyze a local WARC collectionmetawarc
Full Wayback-style replay with Wombat/JavaScript fidelitypywb (export CDXJ from metawarc)
Parse or rewrite WARC records in Pythonwarcio (also used inside metawarc)
Capture-time CDX lookup without a catalogCDX/CDXJ files
Fetch live websites into WARCwget --warc-file, Browsertrix, or similar crawlers
Bounded local HTML/CSS replay from an existing indexmetawarc (serve / replay)
Agent/MCP tooling over indexed metadatametawarc (mcp)

metawarc strengths

  • Versioned DuckDB catalog with Parquet sidecars and stable archive IDs
  • Typed, parameterized queries shared by CLI, REST, and MCP
  • Bounded metadata extraction (PDF, OOXML, images, video, audio, fonts, links)
  • Collection analysis: summary, hashes, duplicates, links, integrity
  • Local website replay plus CDXJ export for pywb interop
  • Source WARC files remain immutable; interrupted writes do not publish incomplete sidecars

When another tool wins

  • pywb: full JS rewriting, Wombat, production Wayback UX
  • warcio: library-level record iteration inside your own Python code
  • CDX: capture-time indexes already maintained by a crawler
  • wget / Browsertrix: creating WARCs, not querying them