Comparison
TrueMemory vs agents-from-scratch
Verdict
Pick TrueMemory if trueMemory is an automatic capture and recall memory system for AI agents using SQLite; pick agents-from-scratch if agents-from-scratch is for those who want absolute control over their AI agent development using only local resources and Python, focusing on deep learning without relying on external frameworks or cloud dependencies.
Markdown twin · TrueMemory alternatives · agents-from-scratch alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | TrueMemory | agents-from-scratch |
|---|---|---|
| Maintenance | Active (25d since push) As of today · github_public_v1 | Active (18d since push) As of 1w · github_public_v1 |
| Provenance | Not a fork · Personal account As of today · github_public_v1 | Not a fork · Personal account As of 1w · 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
- TrueMemory
- Automatic capture and recall memory system for AI agents
- agents-from-scratch
- Build AI agents locally without relying on frameworks or cloud APIs.
Stars
- TrueMemory
- 373
- agents-from-scratch
- 954
Forks
- TrueMemory
- 47
- agents-from-scratch
- 240
Open issues
- TrueMemory
- 18
- agents-from-scratch
- 3
Language
- TrueMemory
- Python
- agents-from-scratch
- Python
Adopt for
- TrueMemory
- TrueMemory is an automatic capture and recall memory system for AI agents using SQLite.
- agents-from-scratch
- agents-from-scratch is for those who want absolute control over their AI agent development using only local resources and Python, focusing on deep learning without relying on external frameworks or cloud dependencies.
Persona
- TrueMemory
- -
- agents-from-scratch
- -
Runtime
- TrueMemory
- -
- agents-from-scratch
- -
License
- TrueMemory
- AGPL-3.0
- agents-from-scratch
- MIT License: Permissive licensing allowing free use and distribution for both commercial and non-commercial purposes.
Last pushed
- TrueMemory
- Jul 29, 2026
- agents-from-scratch
- Jul 25, 2026
Categories
- TrueMemory
- AI Agents, Developer Tools
- agents-from-scratch
- AI Agents, Developer Tools
Trust and health
Days since push
- TrueMemory
- 25d
- agents-from-scratch
- 18d
Open issues (now)
- TrueMemory
- 18
- agents-from-scratch
- 3
Stars delta
- TrueMemory
- +4 (30d)
- agents-from-scratch
- Unknown
Open issues delta
- TrueMemory
- +5 (30d)
- agents-from-scratch
- Unknown
Full report
- TrueMemory
- Trust report
- agents-from-scratch
- Trust report
Choose TrueMemory if…
- License: TrueMemory is AGPL-3.0, agents-from-scratch is MIT.
- Tags unique to TrueMemory: agent-memory, ai-agent, embeddings, generative-ai.
- When you want to ensure your memory storage remains entirely local without depending on cloud services.
When NOT to use TrueMemory
- If you need extensive scalability features offered by cloud-based memory solutions.
- When your project mandates integration exclusively with non-SQLite databases, because TrueMemory is centered around SQLite for its backend.
Choose agents-from-scratch if…
- License: agents-from-scratch is MIT, TrueMemory is AGPL-3.0.
- Requirements: Min 8 GB RAM; Local large language model availability is critical as the tool does not utilize any cloud APIs..
- Tags unique to agents-from-scratch: agent-architecture, ai-agents, local-llm, no-framework.
- You plan to teach yourself or others about the fundamentals of creating AI agents from ground zero with complete transparency into each layer of architecture.
When NOT to use agents-from-scratch
- You are working on an application that needs to be deployed quickly. The tool's approach from first principles can be time-consuming compared to using established frameworks.
- If you need scalability or cloud capabilities such as easy scaling with demand, this tool will not provide these features since it strictly operates on local infrastructure.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (buildingjoshbetter/TrueMemory) · observed Aug 23, 2026
- GitHub forks (buildingjoshbetter/TrueMemory) · observed Aug 23, 2026
- Last push (buildingjoshbetter/TrueMemory) · observed Jul 29, 2026
- License file (AGPL-3.0) · observed Aug 23, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (pguso/agents-from-scratch) · observed Aug 12, 2026
- GitHub forks (pguso/agents-from-scratch) · observed Aug 12, 2026
- Last push (pguso/agents-from-scratch) · observed Jul 25, 2026
- License file (MIT) · observed Aug 12, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: TrueMemory 373 · agents-from-scratch 954 (synced Aug 23, 2026).
Common questions
- What is the difference between TrueMemory and agents-from-scratch?
- TrueMemory: Automatic capture and recall memory system for AI agents. agents-from-scratch: Build AI agents locally without relying on frameworks or cloud APIs.. See the comparison table for live GitHub stats and shared categories.
- When should I choose TrueMemory over agents-from-scratch?
- Choose TrueMemory over agents-from-scratch when License: TrueMemory is AGPL-3.0, agents-from-scratch is MIT; Tags unique to TrueMemory: agent-memory, ai-agent, embeddings, generative-ai; When you want to ensure your memory storage remains entirely local without depending on cloud services.
- When should I choose agents-from-scratch over TrueMemory?
- Choose agents-from-scratch over TrueMemory when License: agents-from-scratch is MIT, TrueMemory is AGPL-3.0; Requirements: Min 8 GB RAM; Local large language model availability is critical as the tool does not utilize any cloud APIs.; Tags unique to agents-from-scratch: agent-architecture, ai-agents, local-llm, no-framework; You plan to teach yourself or others about the fundamentals of creating AI agents from ground zero with complete transparency into each layer of architecture.
- When should I avoid TrueMemory?
- If you need extensive scalability features offered by cloud-based memory solutions. When your project mandates integration exclusively with non-SQLite databases, because TrueMemory is centered around SQLite for its backend.
- When should I avoid agents-from-scratch?
- You are working on an application that needs to be deployed quickly. The tool's approach from first principles can be time-consuming compared to using established frameworks. If you need scalability or cloud capabilities such as easy scaling with demand, this tool will not provide these features since it strictly operates on local infrastructure.
- Is TrueMemory or agents-from-scratch more popular on GitHub?
- agents-from-scratch has more GitHub stars (954 vs 373). Stars measure visibility, not whether either tool fits your constraints.
- Are TrueMemory and agents-from-scratch open source?
- Yes - both are open-source projects on GitHub (TrueMemory: AGPL-3.0, agents-from-scratch: MIT).
- Where can I find alternatives to TrueMemory or agents-from-scratch?
- GraphCanon lists graph-backed alternatives at TrueMemory alternatives and agents-from-scratch alternatives (TrueMemory markdown twin, agents-from-scratch 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, TrueMemory or agents-from-scratch?
- TrueMemory: Active. agents-from-scratch: 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 TrueMemory and agents-from-scratch?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: TrueMemory trust report; agents-from-scratch trust report.