Synapse Layer — Continuous Consciousness Infrastructure

<!-- mcp-name: io.github.SynapseLayer/synapse-layer --> <div align="center">

🧠 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.

       

Website · Docs · PyPI · Forge

</div>

---

⚡ 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.

---

License

Apache-2.0 © Synapse Layer