--- title: "mengram vs openagent" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/alibaizhanov-mengram-vs-the-open-agent-openagent" tools: ["alibaizhanov-mengram", "the-open-agent-openagent"] --- # mengram vs openagent *GraphCanon updated Sep 27, 2026* ## Verdict Pick mengram if mengram provides human-like memory capabilities for AI agents, including semantic, episodic, and procedural memory, enabling learning from experiences and failures. It offers free API access, Python and JS SDKs, and is a; pick openagent if next-generation personal AI assistant powered by LLM, RAG and agent loops focusing on tasks like computer-use, browser navigation, coding support with an. [mengram](https://mengram.io) reports 196 GitHub stars, 34 forks, and 25 open issues, last pushed Sep 16, 2026. [openagent](https://openagentai.org) has 5.6k stars, 657 forks, and 45 open issues, last pushed Sep 17, 2026. Figures are from public GitHub metadata via [mengram's repository](https://github.com/alibaizhanov/mengram) and [openagent's repository](https://github.com/the-open-agent/openagent). | | [mengram](/tools/alibaizhanov-mengram.md) | [openagent](/tools/the-open-agent-openagent.md) | | --- | --- | --- | | Tagline | Human-like memory for AI agents | next-generation personal AI assistant powered by LLM, RAG and agent loops | | Stars | 196 | 5,628 | | Forks | 34 | 657 | | Open issues | 25 | 45 | | Language | Python | Go | | Adopt for | mengram provides human-like memory capabilities for AI agents, including semantic, episodic, and procedural memory, enabling learning from experiences and failures. It offers free API access, Python and JS SDKs, and is a | next-generation personal AI assistant powered by LLM, RAG and agent loops focusing on tasks like computer-use, browser navigation, coding support with an emphasis on Go language | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | AI Agents, Data & Retrieval | AI Agents, Data & Retrieval, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [mengram](/tools/alibaizhanov-mengram.md) | [openagent](/tools/the-open-agent-openagent.md) | | --- | --- | --- | | Days since push | 1d | 2d | | Open issues (now) | 25 | 45 | | Stars delta | +12 (30d) | +176 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/alibaizhanov-mengram/trust.md) | [trust report](/tools/the-open-agent-openagent/trust.md) | ## Decision facts: mengram - **Adopt for:** mengram provides human-like memory capabilities for AI agents, including semantic, episodic, and procedural memory, enabling learning from experiences and failures. It offers free API access, Python and JS SDKs, and is a ## Decision facts: openagent - **Adopt for:** next-generation personal AI assistant powered by LLM, RAG and agent loops focusing on tasks like computer-use, browser navigation, coding support with an emphasis on Go language ## Choose when ### Choose mengram if… - mengram is primarily Python; openagent is Go. - Tags unique to mengram: agent-memory, ai-agents, ai-memory, claude-desktop. - When you need an AI agent that can learn from its experiences and failures, leveraging semantic, episodic, and procedural memory capabilities. ### Choose openagent if… - openagent is primarily Go; mengram is Python. - Tags unique to openagent: agent, agentic-ai, agi, chatbot. - Also covers LLM Frameworks. - When needing advanced coding assistance, offering deep integration with the Go programming environment ## When NOT to use mengram - If your project does not require the specific memory capabilities of semantic, episodic, and procedural memory, mengram might offer more features than necessary. - If you are looking for a tool that does not require the setup of an MCP server, mengram might not be the best fit as it involves configuring this server. - For projects that do not need integration with LangChain, CrewAI, or OpenClaw, the specific integrations provided by mengram may not be beneficial. - If your AI agent development does not benefit from the use of pgvector, mengram's recent debugging efforts in this area may not be relevant to your needs. ## When NOT to use openagent - If looking for broader language support beyond the focus on Go, as openagent may not cater to other programming languages or frameworks as seamlessly - In environments where real-time performance is critical, as its reliance on LLM and RAG might introduce latency ## Common questions ### What is the difference between mengram and openagent? mengram: Human-like memory for AI agents. openagent: next-generation personal AI assistant powered by LLM, RAG and agent loops. See the comparison table for live GitHub stats and shared categories. ### When should I choose mengram over openagent? Choose mengram over openagent when mengram is primarily Python; openagent is Go; Tags unique to mengram: agent-memory, ai-agents, ai-memory, claude-desktop; When you need an AI agent that can learn from its experiences and failures, leveraging semantic, episodic, and procedural memory capabilities. ### When should I choose openagent over mengram? Choose openagent over mengram when openagent is primarily Go; mengram is Python; Tags unique to openagent: agent, agentic-ai, agi, chatbot; Also covers LLM Frameworks; When needing advanced coding assistance, offering deep integration with the Go programming environment. ### When should I avoid mengram? If your project does not require the specific memory capabilities of semantic, episodic, and procedural memory, mengram might offer more features than necessary. If you are looking for a tool that does not require the setup of an MCP server, mengram might not be the best fit as it involves configuring this server. For projects that do not need integration with LangChain, CrewAI, or OpenClaw, the specific integrations provided by mengram may not be beneficial. If your AI agent development does not benefit from the use of pgvector, mengram's recent debugging efforts in this area may not be relevant to your needs. ### When should I avoid openagent? If looking for broader language support beyond the focus on Go, as openagent may not cater to other programming languages or frameworks as seamlessly In environments where real-time performance is critical, as its reliance on LLM and RAG might introduce latency ### Is mengram or openagent more popular on GitHub? openagent has more GitHub stars (5,628 vs 196). Stars measure visibility, not whether either tool fits your constraints. ### Are mengram and openagent open source? Yes - both are open-source projects on GitHub (mengram: Apache-2.0, openagent: Apache-2.0). ### Where can I find alternatives to mengram or openagent? GraphCanon lists graph-backed alternatives at [mengram alternatives](/tools/alibaizhanov-mengram/alternatives) and [openagent alternatives](/tools/the-open-agent-openagent/alternatives) ([mengram markdown twin](/tools/alibaizhanov-mengram/alternatives.md), [openagent markdown twin](/tools/the-open-agent-openagent/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-the-open-agent-openagent.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, mengram or openagent? mengram: Very active. openagent: 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 openagent? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [mengram trust report](/tools/alibaizhanov-mengram/trust); [openagent trust report](/tools/the-open-agent-openagent/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/_