🧠 Synapse Layer

Name: Synapse Layer — Trust Infrastructure for AI Agents
Author: synapselayer

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

⚡ 30-Second Quickstart

pip install synapse-layer

from 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 → 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

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 → Dashboard → Connect

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.

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.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.

Synapse Layer — Trust Infrastructure for AI Agents