memoripy vs OpenViking

AI agent memory and context projects compared

memoripy and OpenViking both provide persistent context for AI agents, with scoped retrieval and local or self-hosted use. memoripy emphasizes evidence tracking, changing facts, and cited recall, while OpenViking organizes documents, memories, and skills in a browsable virtual filesystem.

memoripyOpenViking
LanguagePythonPython
LicenseApache-2.0AGPL-3.0
Stars69439.2k
Forks593.1k
Last analyzedOct 9, 2026Oct 3, 2026

Key differences

  • memoripy screens incoming evidence, tracks versioned and time-sensitive facts, and provides citations; OpenViking organizes resources, memories, and skills under browsable `viking://` paths.
  • memoripy provides admission policies, audit tools, and correction and deletion history; OpenViking offers file-like operations, generated overviews, and session archiving with editable memory extraction.
  • memoripy's core needs no external model or database, with PostgreSQL and model providers optional; OpenViking self-hosting requires a model provider with embedding and vision-language models.
  • memoripy is licensed under Apache-2.0; OpenViking is licensed under AGPL-3.0, with component licenses and distribution requirements worth checking.
  • memoripy is a local Python library with optional service and MCP interfaces; OpenViking also offers a hosted service, web studio, HTTP API, CLI, and SDKs for Python, Go, and TypeScript.
  • memoripy notes that v4 is under development and its stable PyPI API may differ; OpenViking describes local and production deployment and recommends configuring authentication before exposing a server beyond localhost.

Choose memoripy if you…

  • need auditable memory with evidence, citations, and historical versions of changing facts.
  • want admission policies and CLI audits to catch unsupported claims, conflicts, sensitive data, or citation gaps.
  • prefer a core runtime that does not require an external model or database.
Read the memoripy analysis →

Choose OpenViking if you…

  • want to browse and manage agent context as files in a virtual filesystem.
  • need to organize documents, memories, and skills and scope retrieval to a project directory or subtree.
  • want available integrations, SDKs, or a hosted service alongside self-hosting options.
Read the OpenViking analysis →

This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.

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