FootprintAI/Containarium vs doobidoo/mcp-memory-service
Based on the latest public GitHub metadata. No paid placement influences this comparison.
FootprintAI/Containarium has the stronger current discovery signal, driven by the score components shown below.
FootprintAI/Containarium is categorized as Agent Infrastructure; doobidoo/mcp-memory-service is categorized as Agent Infrastructure. Compare their product descriptions and source repositories before choosing.
| Signal | FootprintAI/Containarium | doobidoo/mcp-memory-service |
|---|---|---|
| Radar Score | 81/100 | 76/100 |
| Adoption | 16/25 | 19/25 |
| Maintenance | 25/20 | 20/20 |
| Project quality | 20/20 | 17/20 |
| Agent relevance | 20/20 | 20/20 |
| Demand evidence | 0/10 | 0/10 |
| Observed momentum | 0/5 | 0/5 |
| GitHub stars | 277 | 1,926 |
| Category | Agent Infrastructure | Agent Infrastructure |
FootprintAI/Containarium
Open-source agent runtime — SSH-native isolation, eBPF egress policy, Kubernetes + LXC backends, GPU passthrough, MCP-native CLI
Full analysisdoobidoo/mcp-memory-service
Open-source persistent memory for AI agent pipelines (LangGraph, CrewAI, AutoGen) and Claude. REST API + knowledge graph + autonomous consolidation.
Full analysisTransparent scoring
Adoption (25 points) uses stars and forks, maintenance (20) uses code activity, quality (20) checks license and metadata, relevance (20) checks agent focus, demand (10) uses open Issues, and momentum (5) uses star growth.