⚡ 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.

Why Synapse Layer?

Your AI agents forget everything between sessions. Synapse Layer fixes that — in one line.

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:

• 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

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

See SECURITY.md for vulnerability reporting.

Related Projects

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