Comparison
mengram vs hello-agents
Verdict
Pick mengram if mengram offers memory functionalities tailored for AI agents, including semantic, episodic, and procedural capabilities with integrations into platforms like LangChain, CrewAI, and OpenClaw; pick hello-agents if hello-agents is a comprehensive guide and hands-on tutorial for developing AI agents using LLMs (Large Language Models) and RAG methods.
Markdown twin · mengram alternatives · hello-agents alternatives
GraphCanon updated today
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Trust & integrity
| Signal | mengram | hello-agents |
|---|---|---|
| Maintenance | Active (24d since push) As of today · github_public_v1 | Very active (0d since push) As of 1d · github_public_v1 |
| Provenance | Not a fork · Personal account As of today · github_public_v1 | Not a fork · Organization account As of 1d · github_public_v1 |
| Security (OSV) | 23 low (23 low) As of today · osv@v1 | No lockfile As of 1d · none |
Tagline
- mengram
- Human-like memory for AI agents — semantic, episodic & procedural.
- hello-agents
- Course on building intelligent agents from scratch
Stars
- mengram
- 183
- hello-agents
- 65k
Forks
- mengram
- 26
- hello-agents
- 8.1k
Open issues
- mengram
- 20
- hello-agents
- 144
Language
- mengram
- Python
- hello-agents
- Python
Adopt for
- mengram
- Mengram offers memory functionalities tailored for AI agents, including semantic, episodic, and procedural capabilities with integrations into platforms like LangChain, CrewAI, and OpenClaw.
- hello-agents
- hello-agents is a comprehensive guide and hands-on tutorial for developing AI agents using LLMs (Large Language Models) and RAG methods.
Persona
- mengram
- -
- hello-agents
- -
Runtime
- mengram
- -
- hello-agents
- -
License
- mengram
- Apache-2.0
- hello-agents
- hello-agents is covered under an unconventional license which may require further review before usage.
Last pushed
- mengram
- Jun 17, 2026
- hello-agents
- Jul 10, 2026
Categories
- mengram
- AI Agents, Evaluation & Observability
- hello-agents
- AI Agents, LLM Frameworks
Trust and health
Maintenance
- mengram
- Active (82%)
- hello-agents
- Very active (96%)
Days since push
- mengram
- 24d
- hello-agents
- 0d
Open issues (now)
- mengram
- 20
- hello-agents
- 144
Owner type
- mengram
- User
- hello-agents
- Organization
Security scan
- mengram
- 23 low (23 low)
- hello-agents
- No lockfile
Full report
- mengram
- Trust report
- hello-agents
- Trust report
Choose mengram if…
- License: mengram is Apache-2.0, hello-agents is Other.
- Tags unique to mengram: agent-memory, ai-agents, ai-memory, cognitive-architecture.
- Also covers Evaluation & Observability.
- mengram ships Docker support for self-hosted deployment.
- Use Mengram if your project requires a comprehensive suite of human-like memory capabilities (semantic, episodic, procedural) for AI agents.
When NOT to use mengram
- Avoid Mengram if your project focuses solely on a specific type of memory (e.g., only semantic) and requires more specialized functionality not provided by Mengram.
- Mengram might be less appealing if direct terminal access is preferred over the provided one-prompt setup method, which some users might deem as more complex or cumbersome.
Choose hello-agents if…
- License: hello-agents is Other, mengram is Apache-2.0.
- Requirements: Min 4 GB RAM; Python knowledge assumed.
- Tags unique to hello-agents: agent, llm, rag, tutorial.
- Also covers LLM Frameworks.
- You should use hello-agents if you are interested in practical, step-by-step instructions on building intelligent agents from the ground up.
When NOT to use hello-agents
- Avoid using hello-agents if you are looking for a quick, superficial introduction to AI agents; this tool focuses heavily on in-depth learning and practical application.
- Do not opt for hello-agents if you want a more general AI development resource; unlike some competitors, it has a narrower focus specifically on agent creation with advanced methods like LLMs and RAG.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (alibaizhanov/mengram) · observed Jul 11, 2026
- GitHub forks (alibaizhanov/mengram) · observed Jul 11, 2026
- Last push (alibaizhanov/mengram) · observed Jun 17, 2026
- License file (Apache-2.0) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (datawhalechina/hello-agents) · observed Jul 11, 2026
- GitHub forks (datawhalechina/hello-agents) · observed Jul 11, 2026
- Last push (datawhalechina/hello-agents) · observed Jul 10, 2026
- License file (Other) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: mengram 183 · hello-agents 65k (synced Jul 11, 2026).
Common questions
- What is the difference between mengram and hello-agents?
- mengram: Human-like memory for AI agents — semantic, episodic & procedural.. hello-agents: Course on building intelligent agents from scratch. See the comparison table for live GitHub stats and shared categories.
- When should I choose mengram over hello-agents?
- Choose mengram over hello-agents when License: mengram is Apache-2.0, hello-agents is Other; Tags unique to mengram: agent-memory, ai-agents, ai-memory, cognitive-architecture; Also covers Evaluation & Observability; mengram ships Docker support for self-hosted deployment; Use Mengram if your project requires a comprehensive suite of human-like memory capabilities (semantic, episodic, procedural) for AI agents.
- When should I choose hello-agents over mengram?
- Choose hello-agents over mengram when License: hello-agents is Other, mengram is Apache-2.0; Requirements: Min 4 GB RAM; Python knowledge assumed; Tags unique to hello-agents: agent, llm, rag, tutorial; Also covers LLM Frameworks; You should use hello-agents if you are interested in practical, step-by-step instructions on building intelligent agents from the ground up.
- When should I avoid mengram?
- Avoid Mengram if your project focuses solely on a specific type of memory (e.g., only semantic) and requires more specialized functionality not provided by Mengram. Mengram might be less appealing if direct terminal access is preferred over the provided one-prompt setup method, which some users might deem as more complex or cumbersome.
- When should I avoid hello-agents?
- Avoid using hello-agents if you are looking for a quick, superficial introduction to AI agents; this tool focuses heavily on in-depth learning and practical application. Do not opt for hello-agents if you want a more general AI development resource; unlike some competitors, it has a narrower focus specifically on agent creation with advanced methods like LLMs and RAG.
- Is mengram or hello-agents more popular on GitHub?
- hello-agents has more GitHub stars (65,432 vs 183). Stars measure visibility, not whether either tool fits your constraints.
- Are mengram and hello-agents open source?
- Yes - both are open-source projects on GitHub (mengram: Apache-2.0, hello-agents: Other).
- Where can I find alternatives to mengram or hello-agents?
- GraphCanon lists graph-backed alternatives at mengram alternatives and hello-agents alternatives (mengram markdown twin, hello-agents 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, mengram or hello-agents?
- mengram: Active. hello-agents: 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 mengram and hello-agents?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: mengram trust report; hello-agents trust report.