For developers building AI agents, Supermemory is a semantic memory API that stores and retrieves context so agents can recall prior interactions instead of starting fresh each time.
Presence & Market Position
Tracked · below panel floor — earned mentions are accruing toward the next scored window.
Measures earned, engagement-weighted share of voice across the GTM voices panel. Methodology →
Supermemory is working to own the persistent context layer for AI agents, giving developers managed memory and semantic retrieval across conversations and applications. Its market presence is early and technical, with practitioner discussion moving between concrete agent workflows and head-to-head retrieval evaluations. Recent product activity has widened the story from per-agent recall to company knowledge through shared context, team permission controls, and a Slack-based company brain. The mix keeps Supermemory close to the infrastructure debate over how agents remember users, prior work, and organizational context across sessions.
Clearskies
Turso
Zep
Mem0
VascoComposio, Cluely, Scira, Montra, Rets
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Business Profile
Founded in 2024, Supermemory is an independent 13-person company with $3M in recorded funding. It began as a consumer app and open-source project, then turned the underlying infrastructure into a commercial memory service after developers asked to build on it. The current product covers agent memory, content extraction, connectors, semantic search, and managed retrieval. That path puts a small, recently funded team behind an API-first context layer used across personal agents, product integrations, and company knowledge workflows.
Agent Readiness
Measures how easily your agents can build on it — API, MCP, CLI, SDK, docs depth. Methodology →
Supermemory ships API, MCP, and SDK surfaces for persistent agent context. Its Python and TypeScript SDKs let developers add and retrieve memories, while the MCP server can save, forget, recall, and inject profile context across compatible assistants. Project scoping, OAuth or API-key authentication, and container-based isolation support multi-user deployments. Recent team controls extend the same memory layer from individual assistants to shared organizational context.
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