Comparison
deep-searcher vs memsearch
Verdict
Pick deep-searcher if deepSearcher is an open-source tool for reasoning and searching on private data, using vector databases and LLM integrations in Python under Apache-2.0 license; pick memsearch if memsearch is a hybrid memory management solution for AI agents with Markdown and Milvus backing, ideal for rich semantic search and long-term data storage.
Markdown twin · deep-searcher alternatives · memsearch alternatives
GraphCanon updated 2d
vs
Trust & integrity
| Signal | deep-searcher | memsearch |
|---|---|---|
| Maintenance | Slowing (272d since push) As of 2d · github_public_v1 | Very active (0d since push) As of 4w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2d · github_public_v1 | Not a fork · Organization account As of 4w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- deep-searcher
- Open Source Deep Research Alternative to Reason and Search on Private Data.
- memsearch
- A persistent, unified memory layer for all your AI agents backed by Markdown and Milvus.
Stars
- deep-searcher
- 8.1k
- memsearch
- 2.3k
Forks
- deep-searcher
- 775
- memsearch
- 205
Open issues
- deep-searcher
- 53
- memsearch
- 231
Language
- deep-searcher
- Python
- memsearch
- Python
Adopt for
- deep-searcher
- DeepSearcher is an open-source tool for reasoning and searching on private data, using vector databases and LLM integrations in Python under Apache-2.0 license.
- memsearch
- memsearch is a hybrid memory management solution for AI agents with Markdown and Milvus backing, ideal for rich semantic search and long-term data storage.
Persona
- deep-searcher
- -
- memsearch
- -
Runtime
- deep-searcher
- -
- memsearch
- -
License
- deep-searcher
- Apache-2.0
- memsearch
- MIT
Last pushed
- deep-searcher
- Nov 19, 2025
- memsearch
- Jul 22, 2026
Categories
- deep-searcher
- AI Agents, LLM Frameworks, Vector Databases
- memsearch
- AI Agents, Data & Retrieval, Vector Databases
Trust and health
Maintenance
- deep-searcher
- Slowing (36%)
- memsearch
- Very active (96%)
Days since push
- deep-searcher
- 272d
- memsearch
- 0d
Open issues (now)
- deep-searcher
- 53
- memsearch
- 231
Stars delta
- deep-searcher
- +59 (30d)
- memsearch
- Unknown
Open issues delta
- deep-searcher
- 0 (30d)
- memsearch
- Unknown
Full report
- deep-searcher
- Trust report
- memsearch
- Trust report
Choose deep-searcher if…
- License: deep-searcher is Apache-2.0, memsearch is MIT.
- Tags unique to deep-searcher: agent, agentic-rag, deep-research, llm.
- Also covers LLM Frameworks.
- deep-searcher ships Docker support for self-hosted deployment.
- When you require custom search and reasoning capabilities on your private datasets with integration of multiple LLMs like Claude or Qwen3.
When NOT to use deep-searcher
- Avoid if your project demands proprietary solutions, as DeepSearcher is open-source and may not be suitable for closed systems.
- Not ideal when a single vector database suffices; DeepSearcher supports multiple databases which might be overkill and complicate setup unnecessarily.
Choose memsearch if…
- License: memsearch is MIT, deep-searcher is Apache-2.0.
- Tags unique to memsearch: agent-memory, long-term-memory, milvus, semantic-search.
- Also covers Data & Retrieval.
- When you need robust integration with AI agents like Claude Code or Codex
When NOT to use memsearch
- If your application doesn't require integration with specific AI agents like Claude Code
- In cases where only simple text data storage without semantic search is needed
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (zilliztech/deep-searcher) · observed Aug 18, 2026
- GitHub forks (zilliztech/deep-searcher) · observed Aug 18, 2026
- Last push (zilliztech/deep-searcher) · observed Nov 19, 2025
- License file (Apache-2.0) · observed Aug 18, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (zilliztech/memsearch) · observed Jul 22, 2026
- GitHub forks (zilliztech/memsearch) · observed Jul 22, 2026
- Last push (zilliztech/memsearch) · observed Jul 22, 2026
- License file (MIT) · observed Jul 22, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: deep-searcher 8.1k · memsearch 2.3k (synced Aug 18, 2026).
Common questions
- What is the difference between deep-searcher and memsearch?
- deep-searcher: Open Source Deep Research Alternative to Reason and Search on Private Data.. memsearch: A persistent, unified memory layer for all your AI agents backed by Markdown and Milvus.. See the comparison table for live GitHub stats and shared categories.
- When should I choose deep-searcher over memsearch?
- Choose deep-searcher over memsearch when License: deep-searcher is Apache-2.0, memsearch is MIT; Tags unique to deep-searcher: agent, agentic-rag, deep-research, llm; Also covers LLM Frameworks; deep-searcher ships Docker support for self-hosted deployment; When you require custom search and reasoning capabilities on your private datasets with integration of multiple LLMs like Claude or Qwen3.
- When should I choose memsearch over deep-searcher?
- Choose memsearch over deep-searcher when License: memsearch is MIT, deep-searcher is Apache-2.0; Tags unique to memsearch: agent-memory, long-term-memory, milvus, semantic-search; Also covers Data & Retrieval; When you need robust integration with AI agents like Claude Code or Codex.
- When should I avoid deep-searcher?
- Avoid if your project demands proprietary solutions, as DeepSearcher is open-source and may not be suitable for closed systems. Not ideal when a single vector database suffices; DeepSearcher supports multiple databases which might be overkill and complicate setup unnecessarily.
- When should I avoid memsearch?
- If your application doesn't require integration with specific AI agents like Claude Code In cases where only simple text data storage without semantic search is needed
- Is deep-searcher or memsearch more popular on GitHub?
- deep-searcher has more GitHub stars (8,060 vs 2,336). Stars measure visibility, not whether either tool fits your constraints.
- Are deep-searcher and memsearch open source?
- Yes - both are open-source projects on GitHub (deep-searcher: Apache-2.0, memsearch: MIT).
- Where can I find alternatives to deep-searcher or memsearch?
- GraphCanon lists graph-backed alternatives at deep-searcher alternatives and memsearch alternatives (deep-searcher markdown twin, memsearch markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, deep-searcher or memsearch?
- deep-searcher: Slowing. memsearch: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for deep-searcher and memsearch?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: deep-searcher trust report; memsearch trust report.