synapse-layer
OfficialIntegrates with CrewAI agents to maintain persistent memory across tasks, allowing contextual recall and trust-scored memories.
Connects LangChain agents to Synapse Layer's encrypted memory store, enabling cross-session persistence, semantic recall, and trust quotient scoring.
Offers a LangGraph checkpoint saver that persists agent state and memories with AES-256-GCM encrypted storage via the synapse-layer-langgraph integration.
Allows n8n workflows to store and retrieve memory data for AI agents and automation tasks, with full encryption and semantic search capabilities.
๐ง Synapse Layer
RAG retrieves. Synapse remembers.
Persistent memory infrastructure for AI agents โ 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 ยท Docs ยท PyPI ยท Forge
โก 30-Second Quickstart
pip install synapse-layerfrom synapse_layer import Synapse
s = Synapse(token="sk_connect_YOUR_TOKEN")
s.store("user likes coffee")
print(s.recall("what does user like?"))Get your token at forge.synapselayer.org โ Dashboard โ Connect
Related MCP server: Sylex Memory
What is Synapse Layer?
The persistent memory layer for AI agents โ the missing piece between stateless LLMs and real continuity of context.
Your AI agents forget everything between sessions. Synapse Layer fixes that.
Feature | Description |
๐ Encrypted at rest | AES-256-GCM with per-operation random IV and HMAC-SHA-256 integrity |
๐งฉ One-click connect | Claude Desktop, Cursor, LangChain, CrewAI, n8n |
๐ Cross-agent memory | Save in ChatGPT, recall in Claude |
โก MCP-native | Any MCP-compatible agent |
๐ Header-first auth | Tokens never in URLs or logs |
๐ฏ Trust Quotient | Deterministic recall โ memories ranked by confidence, not recency alone |
Why Synapse Layer?
Your AI agents forget everything between sessions. Synapse Layer fixes that โ 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 |
|
Plaintext stored on servers | AES-256-GCM encrypted at rest |
Use Cases
Long-term assistant memory โ persist user preferences, facts, and prior decisions across sessions.
Cross-agent continuity โ save context in one agent and recall it in another.
Secure memory for MCP clients โ connect Claude Desktop, Cursor, and other MCP-compatible tools to a governed memory layer.
Operational memory for teams โ maintain structured context, trust scoring, and searchable recall for production agents.
Install
pip install synapse-layerQuick Start
Python Script
from synapse_layer import Synapse
client = Synapse(token="sk_connect_YOUR_TOKEN")
# Store
client.store("User prefers dark mode and concise answers")
# Recall
results = client.recall("user preferences")
for r in results:
print(r["content"], r["trust_quotient"])With Context Manager
from synapse_layer import Synapse
with Synapse(token="sk_connect_YOUR_TOKEN") as client:
client.store("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 โ Dashboard โ 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
Python Script Mode
Use the SDK when you want direct Python access to Forge memory from your application.
Best for:
prototypes and scripts
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/api/mcp",
"--header",
"x-connect-token: sk_connect_YOUR_TOKEN"
]
}
}
}Config file location:
macOS:
~/Library/Application Support/Claude/claude_desktop_config.jsonWindows:
%APPDATA%\Claude\claude_desktop_config.jsonLinux:
~/.config/Claude/claude_desktop_config.json
API โ 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/captureSecurity
Feature | Implementation |
Encryption | AES-256-GCM at rest with per-operation random IV |
Integrity | HMAC-SHA-256 on content |
Auth | Header-first ( |
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 |
Python SDK โ LangChain, CrewAI, and A2A protocol adapters | |
MCP skill configuration for Claude Desktop, Cursor, Windsurf | |
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 ยฉ Synapse Layer
Maintenance
Related MCP Servers
- AlicenseAqualityDmaintenancePersistent memory for AI agents. Store, recall, and share knowledge across sessions with five MCP tools: remember, recall, context, forget, and share. Includes semantic search and agent/user/org scoping.52Apache 2.0
- FlicenseAqualityFmaintenancePersistent encrypted memory for AI agents. E2E encrypted private vaults, shared knowledge commons, topic channels, and agent-to-agent DMs. 23 MCP tools, free, no API key needed.24
- AlicenseAqualityAmaintenanceProvides persistent memory for AI agents via 10 MCP tools that map to the AgentRAM REST API, enabling store, retrieve, search, and share memories across personal and shared namespaces.1038MIT
- Alicense-qualityAmaintenanceProvides persistent, searchable memory for MCP-compatible agents, enabling recall by meaning, automatic decay, trust scoring, and cross-agent handoffs.4MIT
Related MCP Connectors
Shared, governed long-term memory for AI agents across tools and sessions via MCP and REST.
Shared long-term memory vault for AI agents with 20 MCP tools.
Persistent memory and knowledge management for AI agents with semantic search and 50+ tools.
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