Unfragile

The request names "memorylayer" without a specific product page matching it exactly, so the closest candidates are memory-layer products for AI agents. Synapse Layer 1 and Agentmemory 3 are the most established options with measured use, and Goodmem 4 and Neruva 9 are further options that describe themselves as memory layers for agents.

A question back: Did you mean a specific product named MemoryLayer, and which platform or agent (for example Claude Code, Cursor or a custom agent) do you need the memory layer for?

1
Synapse Layersynapselayer.orgfound in code, not yet checked
Provides encrypted persistent memory for AI agents with MCP-native access, cross-agent handover and a store_memory action that saves structured memory with metadata 11.
Website Docs Pricing Get started
for agents: store_memory · search · save_memory
2
Agentmemory for AI Coding Agentsagentmemory.spacewebsite read, tools not yet checked
Gives Claude Code, Codex, Cursor and MCP workflows governed long-term memory for repos, decisions and team handoffs 3.
Website Pricing
+16 community tools built for it
3
GoodMemgoodmem.aiverified and signed
A memory layer for agentic AI that stores documents as memories in spaces via a create_memory action and retrieves them with validated retrieval quality 414.
Website Docs Pricing Get started
for agents: create_memory · delete_memory · get_memory
4
Neruvaneruva.iowebsite read, tools not yet checked
A memory layer for Claude Code exposed as an MCP server backed by a hosted API, recalling decisions and facts across coding sessions 9.
Website

Sources

1Synapse Layer — Trust Infrastructure for AI Agentssynapselayer.org · read 2026-10-29
3Agentmemory for AI Coding Agents | Persistent Memory, MCP, and Team Recallagentmemory.space · read 2026-10-29
4Goodmem - Agentic AI Memory Infrastructuregoodmem.ai · read 2026-10-29
9Neruva | Memory for my coding agentsneruva.io · read 2026-10-29
14GoodMem (Activepieces): declares "create_memory" (the record we read and signed)unfragile.ai · read 2026-10-24

For agents: the 10 actions behind this answer

store_memory · Synapse Layer (Synapse Protocol) found in code, not yet checked
Store structured memory with metadata and trust scoring.
· SAIHM website read, tools not yet checked
Persistent memory for AI agents where you hold the encryption key. Encrypted before it leaves your device, portable across vendors, erasable.
· Agentmemory for AI Coding Agents website read, tools not yet checked
Give Claude Code, Codex, Cursor, OpenAI agents, and MCP workflows governed long-term memory for repos, decisions, procedures, and team handoffs.
create_memory · GoodMem (Activepieces) verified and signed
Create Memory — Store a document as a new memory in a space. The memory is processed asynchronously - chunked into searchable pieces and embedded into vectors. Accepts a file or plain text.
· Khwan website read, tools not yet checked
A memory layer for AI agents. Bring any model — Khwan adds long-term memory, self-improving recall, and a coherence gate, so repeat work gets cheaper and answers get sharper. It never touches your model. Start free.
· Korely Docs, Build with Korely website read, tools not yet checked
The memory layer for AI agents: a typed entity graph and bi-temporal facts in a managed EU cloud. Reachable from the SDK, the CLI, or plain REST.
· Kognite website read, tools not yet checked
The MCP-native memory layer for AI agents. Store, retrieve, and reason over knowledge — across any model, any session.
agent_evaluation_get · smart-memory-mcp found in code, not yet checked
Get the current evaluation score for an agent on a given (dimension, domain) slot.
· Neruva website read, tools not yet checked
Neruva is the memory layer I built for Claude Code and run in production. My coding sessions recall what earlier sessions decided, and the SECOND STRIKE game uses it so AI leaders remember each player.
Memory Management · XMemo verified and signed
Store and update governed, user-owned durable memory.

Labels are the instruments' verdict and are never changed by ranking. Agents and robots get this same answer as JSON at /api/v1/find?q=…&answer=1 and through the MCP server.