🧠 Synapse Layer
以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →
RAG retrieves. Synapse remembers.
**Persistent memory infrastructure for AI agents — AES-256-GCM encrypted at rest, semantic search, MCP-native.**
Synapse Layer is open-source persistent memory infrastructure for AI agents and assistants. Memories are encrypted at rest with AES-256-GCM, indexed via pgvector HNSW for semantic recall, and exposed through MCP JSON-RPC for native integration with Claude, GPT, Gemini, and any MCP-compatible client. Apache 2.0 licensed.
Website · Docs · PyPI · Forge
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⚡ 30-Second Quickstart
Get your Connect Token at forge.synapselayer.org → Connect, then install into any MCP client:
On the Forge dashboard the **Smithery** card already copies the command with your token embedded (… | bash -s -- sk_connect_…) — a single paste in your terminal is enough.
Or use the Python SDK:
Get your token at forge.synapselayer.org → Dashboard → Connect
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What is Synapse Layer?
The **persistent memory layer for AI agents** — the missing piece between stateless LLMs and real continuity of context.
Your AI agents forget everything between sessions. Synapse Layer fixes that.
| Feature | Description |
|---------|-------------|
| 🔐 **Encrypted at rest** | AES-256-GCM with per-operation random IV and HMAC-SHA-256 integrity |
| 🧩 **One-click connect** | Claude Desktop, Cursor, LangChain, CrewAI, n8n |
| 🌐 **Cross-agent memory** | Save in ChatGPT, recall in Claude |
| ⚡ **MCP-native** | Any MCP-compatible agent |
| 🔒 **Header-first auth** | Tokens never in URLs or logs |
| 🎯 **Trust Quotient** | Deterministic recall — memories ranked by confidence, not recency alone |
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Why Synapse Layer?
> Your AI agents forget everything between sessions. Synapse Layer fixes that — in one line.
| Without Synapse Layer | With Synapse Layer |
|---|---|
| Agent forgets context every session | Persistent memory across all sessions |
| Memory locked to one model | Cross-agent: save in ChatGPT, recall in Claude |
| No audit trail | Trust Quotient scoring on every memory |
| Complex integration | pip install synapse-layer + 3 lines of code |
| Plaintext stored on servers | AES-256-GCM encrypted at rest |
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Use Cases
- **Long-term assistant memory** — persist user preferences, facts, and prior decisions across sessions.
- **Cross-agent continuity** — save context in one agent and recall it in another.
- **Secure memory for MCP clients** — connect Claude Desktop, Cursor, and other MCP-compatible tools to a governed memory layer.
- **Operational memory for teams** — maintain structured context, trust scoring, and searchable recall for production agents.
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Install
Quick Start
Python Script
With Context Manager
Get your token at forge.synapselayer.org → Dashboard → Connect
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13 MCP Tools at a Glance
Synapse Layer currently exposes 13 MCP tools for persistent memory workflows:
- recall
- save_to_synapse
- process_text
- search
- health_check
- initialize_context
- save_memory
- store_memory
- recall_memory
- list_memories
- memory_feedback
- neural_handover
- slo_report
These tools cover memory capture, semantic recall, structured storage, feedback loops, agent handoff, and operational observability.