--- title: "mengram vs agents-from-scratch" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/alibaizhanov-mengram-vs-pguso-agents-from-scratch" tools: ["alibaizhanov-mengram", "pguso-agents-from-scratch"] --- # mengram vs agents-from-scratch *GraphCanon updated Aug 12, 2026* ## 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 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. [mengram](https://mengram.io) reports 184 GitHub stars, 27 forks, and 27 open issues, last pushed Jul 30, 2026. [agents-from-scratch](https://github.com/pguso/agents-from-scratch) has 954 stars, 240 forks, and 3 open issues, last pushed Jul 25, 2026. Figures are from public GitHub metadata via [mengram's repository](https://github.com/alibaizhanov/mengram) and [agents-from-scratch's repository](https://github.com/pguso/agents-from-scratch). | | [mengram](/tools/alibaizhanov-mengram.md) | [agents-from-scratch](/tools/pguso-agents-from-scratch.md) | | --- | --- | --- | | Tagline | Semantic, episodic, and procedural memory for AI agents, like human记忆被切断了，请稍后尝试重新生成。 | Build AI agents locally without relying on frameworks or cloud APIs. | | Stars | 184 | 954 | | Forks | 27 | 240 | | Open issues | 27 | 3 | | Language | Python | Python | | Adopt for | Mengram offers memory functionalities tailored for AI agents, including semantic, episodic, and procedural capabilities with integrations into platforms like LangChain, CrewAI, and OpenClaw. | 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 | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT License: Permissive licensing allowing free use and distribution for both commercial and non-commercial purposes. | | Categories | AI Agents, Evaluation & Observability | AI Agents, Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [mengram](/tools/alibaizhanov-mengram.md) | [agents-from-scratch](/tools/pguso-agents-from-scratch.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 3d | 18d | | Open issues (now) | 27 | 3 | | Full report | [trust report](/tools/alibaizhanov-mengram/trust.md) | [trust report](/tools/pguso-agents-from-scratch/trust.md) | ## Decision facts: mengram - **Adopt for:** Mengram offers memory functionalities tailored for AI agents, including semantic, episodic, and procedural capabilities with integrations into platforms like LangChain, CrewAI, and OpenClaw. ## Decision facts: agents-from-scratch - **Requirements:** Min 8 GB RAM; Local large language model availability is critical as the tool does not utilize any cloud APIs. - **Adopt for:** 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. - **License detail:** MIT License: Permissive licensing allowing free use and distribution for both commercial and non-commercial purposes. ## Choose when ### Choose mengram if… - License: mengram is Apache-2.0, agents-from-scratch is MIT. - Tags unique to mengram: agent-memory, ai-memory, cognitive-architecture, episodic-memory. - 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. ### Choose agents-from-scratch if… - License: agents-from-scratch is MIT, mengram is Apache-2.0. - 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, llm, local-llm, no-framework. - Also covers Developer Tools. - 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 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 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. ## Common questions ### What is the difference between mengram and agents-from-scratch? mengram: Semantic, episodic, and procedural memory for AI agents, like human记忆被切断了，请稍后尝试重新生成。. 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 mengram over agents-from-scratch? Choose mengram over agents-from-scratch when License: mengram is Apache-2.0, agents-from-scratch is MIT; Tags unique to mengram: agent-memory, ai-memory, cognitive-architecture, episodic-memory; 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 agents-from-scratch over mengram? Choose agents-from-scratch over mengram when License: agents-from-scratch is MIT, mengram is Apache-2.0; 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, llm, local-llm, no-framework; Also covers Developer Tools; 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 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 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 mengram or agents-from-scratch more popular on GitHub? agents-from-scratch has more GitHub stars (954 vs 184). Stars measure visibility, not whether either tool fits your constraints. ### Are mengram and agents-from-scratch open source? Yes - both are open-source projects on GitHub (mengram: Apache-2.0, agents-from-scratch: MIT). ### Where can I find alternatives to mengram or agents-from-scratch? GraphCanon lists graph-backed alternatives at [mengram alternatives](/tools/alibaizhanov-mengram/alternatives) and [agents-from-scratch alternatives](/tools/pguso-agents-from-scratch/alternatives) ([mengram markdown twin](/tools/alibaizhanov-mengram/alternatives.md), [agents-from-scratch markdown twin](/tools/pguso-agents-from-scratch/alternatives.md)), 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](/compare/alibaizhanov-mengram-vs-pguso-agents-from-scratch.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, mengram or agents-from-scratch? mengram: Very 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 mengram and agents-from-scratch? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [mengram trust report](/tools/alibaizhanov-mengram/trust); [agents-from-scratch trust report](/tools/pguso-agents-from-scratch/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=alibaizhanov-mengram`](/api/graphcanon/graph?tool=alibaizhanov-mengram) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_