Editorial take
Why it stands out
Supermemory should be framed as a memory platform for AI builders. The combination of API pricing and plugin access is part of the value story.
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Tool profile
Memory layer and context infrastructure for AI agents, with API access, plugins, retrieval, and persistent user memory across tools and applications.
Agent memory
Supermemory belongs in the database because it is clearly positioned as memory infrastructure for AI systems rather than a consumer note-taking gimmick. The official site describes it as a memory layer for AI agents, with API access, plugins, retrieval, and persistent memory that can power apps, agents, and workflows. That makes it relevant for builders who want memory to be an architectural layer rather than an ad hoc prompt trick.
It also deserves inclusion because the pricing is public, simple, and detailed enough to compare. The official pricing page currently shows Free at $0, Pro at $19 per month, Scale at $399 per month, and Enterprise as custom, while also publishing token and query allowances plus overage rates. That kind of transparency is exactly what serious buyers need.
Quick fit
Editorial take
Supermemory should be framed as a memory platform for AI builders. The combination of API pricing and plugin access is part of the value story.
What it does well
Primary use cases
Fit notes
Compare with
Pressure-test this pick against nearby alternatives.
Agenta
Free planLLMOps
Open-source LLMOps platform for prompt management, evaluation, observability, and collaborative AI application development with a clear hosted pricing ladder.
Choose Agenta when the team wants collaborative prompt management, evals, and observability in one hosted workflow.
Pricing snapshot
Supermemory currently offers Free at $0, Pro at $19 per month, Scale at $399 per month, and Enterprise as custom, with overages at $0.01 per 1,000 tokens and $0.10 per 1,000 queries on paid plans.
AgentOps
Free planAgent observability
Observability for AI agents with tracing, debugging, session visibility, and production monitoring.
Closer to agent observability than to model hosting or prompt tooling
