🧠 Synapse Layer
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.
⚡ 30-Second Quickstart
pip install synapse-layer
from synapse_layer import Synapse
s = Synapse(token="sk_connect_YOUR_TOKEN")
s.save("user likes coffee")
print(s.recall("what does user like?"))
Get your token at forge.synapselayer.org → Dashboard → Connect
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 |
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 |
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.
Install
pip install synapse-layer
Quick Start
Local SDK — in-process memory
import asyncio
from synapse_layer import SynapseClient
async def main():
memory = SynapseClient(agent_id="my-agent")
# Save
await memory.store("User prefers dark mode and concise answers")
# Recall
results = await memory.recall("user preferences")
for r in results:
print(f"[TQ={r.trust_quotient:.2f}] {r.content}")
asyncio.run(main())
Cloud — Forge API (persistent, cross-agent)
from synapse_memory.client import Synapse
client = Synapse(token="sk_connect_YOUR_TOKEN")
client.remember("User prefers dark mode and concise answers")
results = client.recall("user preferences")
for r in results:
print(r["content"])
Get your token at forge.synapselayer.org → Dashboard → Connect
13 MCP Tools at a Glance
Synapse Layer currently exposes 13 MCP tools for persistent memory workflows:
recallsave_to_synapseprocess_textsearchhealth_checkinitialize_contextsave_memorystore_memoryrecall_memorylist_memoriesmemory_feedbackneural_handoverslo_report
These tools cover memory capture, semantic recall, structured storage, feedback loops, agent handoff, and operational observability.
Deployment Modes
Local SDK
Use the local SDK when you want in-process memory access inside your Python application.
Best for:
- local prototypes
- Python-native workflows
- fast integration into existing apps
Cloud / Forge API
Use Forge when you need persistent, cross-session, and cross-agent memory with managed access tokens.
Best for:
- production assistants
- multi-agent systems
- MCP-based integrations
- shared memory across tools and sessions
MCP Integration (Claude Desktop / Cursor)
Add to claude_desktop_config.json:
{
"mcpServers": {
"synapse-layer": {
"command": "npx",
"args": [
"mcp-remote",
"https://forge.synapselayer.org/mcp",
"--header",
"x-connect-token: sk_connect_YOUR_TOKEN"
]
}
}
}
Config file location:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json - Linux:
~/.config/Claude/claude_desktop_config.json
API — Header-First Auth
# Health check
curl -H "x-connect-token: sk_connect_YOUR_TOKEN" \
https://forge.synapselayer.org/api/connect/health
# Save memory
curl -X POST \
-H "x-connect-token: sk_connect_YOUR_TOKEN" \
-H "Content-Type: application/json" \
-d '{"content": "User is a Python developer"}' \
https://forge.synapselayer.org/api/v1/capture
Security
| Feature | Implementation |
|---|---|
| Encryption | AES-256-GCM at rest with per-operation random IV |
| Integrity | HMAC-SHA-256 on content |
| Auth | Header-first (x-connect-token) — tokens never in URLs or logs |
| Privacy | Content sanitization + tenant-scoped encrypted storage |
| Isolation | 1 user = 1 tenant = 1 private mind |
See SECURITY.md for vulnerability reporting.
Related Projects
| Project | Description |
|---|---|
| synapse-sdk-python | Python SDK — LangChain, CrewAI, and A2A protocol adapters |
| synapse-layer-skill | MCP skill configuration for Claude Desktop, Cursor, Windsurf |
| synapse-layer-langgraph | LangGraph checkpoint saver with encrypted state persistence |
Governance
- All public claims follow the Public Claims Matrix.
- Architecture details that reveal benefits are public; mechanisms that enable them are private.
- Claim = Reality. If it's not implemented, it's not in the README.
License
Apache-2.0 © Synapse Layer