synapse-layer
Persistent memory infrastructure for AI agents
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Persistent memory infrastructure for AI agents
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
| name | synapse-layer |
| description | Persistent memory infrastructure for AI agents |
| version | 2.3.7 |
| author | Ismael Marchi |
| tags | ["memory","mcp","ai-agents","llm","typescript","cross-agent"] |
Synapse Layer is a persistent memory infrastructure for AI agents. It solves the stateless-agent problem: agents forget decisions, preferences, and context across sessions. With Synapse, any MCP-compatible agent can store and recall memories — AES-256-GCM encrypted at rest, scored by Trust Quotient for reliability, and scoped per-user with tenant isolation. One agent stores, another recalls. Memory survives across sessions, models, and tools.
MUST:
store() after each interaction that contains a decision, preference, or constraint worth persisting.recall() before responding when the user references prior context, preferences, or past work.tq >= 0.7 when high confidence is required.agent identifier on every store() call for cross-agent traceability.MUST NOT:
recall() first.Trust Quotient is a per-memory confidence score ranging from 0.0 to 1.0.
tq >= 0.7 for high-confidence
decisions. Use tq >= 0.5 for general context. Memories below 0.3 may
contain noise or low-relevance content.Synapse Layer works with any MCP-compatible client: