--- title: "mlx-serve vs claude-mem" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ddalcu-mlx-serve-vs-thedotmack-claude-mem" tools: ["ddalcu-mlx-serve", "thedotmack-claude-mem"] --- # mlx-serve vs claude-mem *GraphCanon updated Jul 15, 2026* ## Verdict Pick mlx-serve when mlx-serve is primarily Zig; claude-mem is JavaScript; pick claude-mem when claude-mem is primarily JavaScript; mlx-serve is Zig. [mlx-serve](http://mlxserve.com/) reports 283 GitHub stars, 22 forks, and 3 open issues, last pushed Jul 14, 2026. [claude-mem](https://claude-mem.ai) has 87k stars, 7.5k forks, and 252 open issues, last pushed Jul 9, 2026. Figures are from public GitHub metadata via [mlx-serve's repository](https://github.com/ddalcu/mlx-serve) and [claude-mem's repository](https://github.com/thedotmack/claude-mem). | | [mlx-serve](/tools/ddalcu-mlx-serve.md) | [claude-mem](/tools/thedotmack-claude-mem.md) | | --- | --- | --- | | Tagline | Native LLM inference server for Apple Silicon. OpenAI + Anthropic API compatible. No Python. Includes MLX Core macOS app with chat, agent mode, and tool calling. | Persistent Context Across Sessions for Every Agent | | Stars | 283 | 86,816 | | Forks | 22 | 7,500 | | Open issues | 3 | 252 | | Language | Zig | JavaScript | | Adopt for | - | claude-mem provides persistent context across sessions, leveraging AI to capture and compress agent activity. | | Persona | - | - | | Runtime | - | - | | License | MIT | Claude-Mem is distributed under the Apache License 2.0, allowing it to be freely used in a variety of development and production environments while maintaining clear licensing terms. | | Categories | AI Agents, Inference & Serving, LLM Frameworks | AI Agents, Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [mlx-serve](/tools/ddalcu-mlx-serve.md) | [claude-mem](/tools/thedotmack-claude-mem.md) | | --- | --- | --- | | Days since push | 0d | 1d | | Open issues (now) | 3 | 252 | | Full report | [trust report](/tools/ddalcu-mlx-serve/trust.md) | [trust report](/tools/thedotmack-claude-mem/trust.md) | ## Decision facts: claude-mem - **Requirements:** Requires Node.js v20.0.0 or higher.; Must have the latest version of Claude Code with plugin support.; Auto-installs Bun (JavaScript runtime and process manager) if not already present.; Requires uv (Python package for vector search), auto-installation supported. - **Adopt for:** claude-mem provides persistent context across sessions, leveraging AI to capture and compress agent activity. - **License detail:** Claude-Mem is distributed under the Apache License 2.0, allowing it to be freely used in a variety of development and production environments while maintaining clear licensing terms. ## Choose when ### Choose mlx-serve if… - mlx-serve is primarily Zig; claude-mem is JavaScript. - License: mlx-serve is MIT, claude-mem is Apache-2.0. - Tags unique to mlx-serve: agent, anthropic-api, apple-silicon, claude code. - Also covers LLM Frameworks. ### Choose claude-mem if… - claude-mem is primarily JavaScript; mlx-serve is Zig. - License: claude-mem is Apache-2.0, mlx-serve is MIT. - Requirements: Requires Node.js v20.0.0 or higher.; Must have the latest version of Claude Code with plugin support.; Auto-installs Bun (JavaScript runtime and process manager) if not already present.; Requires uv (Python package for vector search), auto-installation supported.. - Tags unique to claude-mem: ai-agents, ai-memory, chromadb, claude. - When you require seamless and persistent context continuity between different session interactions with Claude Code or other supported agents. ## When NOT to use mlx-serve - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## When NOT to use claude-mem - When working in environments where Node.js v20.0.0 or higher cannot be installed, as claude-mem requires this version to operate. - If your specific AI agent or tool does not integrate with the supported frameworks listed (e.g., Claude Code, OpenClaw), making context persistence ineffective for your workflow. ## Common questions ### What is the difference between mlx-serve and claude-mem? mlx-serve: Native LLM inference server for Apple Silicon. OpenAI + Anthropic API compatible. No Python. Includes MLX Core macOS app with chat, agent mode, and tool calling.. claude-mem: Persistent Context Across Sessions for Every Agent. See the comparison table for live GitHub stats and shared categories. ### When should I choose mlx-serve over claude-mem? Choose mlx-serve over claude-mem when mlx-serve is primarily Zig; claude-mem is JavaScript; License: mlx-serve is MIT, claude-mem is Apache-2.0; Tags unique to mlx-serve: agent, anthropic-api, apple-silicon, claude code; Also covers LLM Frameworks. ### When should I choose claude-mem over mlx-serve? Choose claude-mem over mlx-serve when claude-mem is primarily JavaScript; mlx-serve is Zig; License: claude-mem is Apache-2.0, mlx-serve is MIT; Requirements: Requires Node.js v20.0.0 or higher.; Must have the latest version of Claude Code with plugin support.; Auto-installs Bun (JavaScript runtime and process manager) if not already present.; Requires uv (Python package for vector search), auto-installation supported.; Tags unique to claude-mem: ai-agents, ai-memory, chromadb, claude; When you require seamless and persistent context continuity between different session interactions with Claude Code or other supported agents. ### When should I avoid mlx-serve? AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### When should I avoid claude-mem? When working in environments where Node.js v20.0.0 or higher cannot be installed, as claude-mem requires this version to operate. If your specific AI agent or tool does not integrate with the supported frameworks listed (e.g., Claude Code, OpenClaw), making context persistence ineffective for your workflow. ### Is mlx-serve or claude-mem more popular on GitHub? claude-mem has more GitHub stars (86,816 vs 283). Stars measure visibility, not whether either tool fits your constraints. ### Are mlx-serve and claude-mem open source? Yes - both are open-source projects on GitHub (mlx-serve: MIT, claude-mem: Apache-2.0). ### Where can I find alternatives to mlx-serve or claude-mem? GraphCanon lists graph-backed alternatives at [mlx-serve alternatives](/tools/ddalcu-mlx-serve/alternatives) and [claude-mem alternatives](/tools/thedotmack-claude-mem/alternatives) ([mlx-serve markdown twin](/tools/ddalcu-mlx-serve/alternatives.md), [claude-mem markdown twin](/tools/thedotmack-claude-mem/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/ddalcu-mlx-serve-vs-thedotmack-claude-mem.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, mlx-serve or claude-mem? mlx-serve: Very active. claude-mem: 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 mlx-serve and claude-mem? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [mlx-serve trust report](/tools/ddalcu-mlx-serve/trust); [claude-mem trust report](/tools/thedotmack-claude-mem/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=ddalcu-mlx-serve`](/api/graphcanon/graph?tool=ddalcu-mlx-serve) - 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/_