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Synapse Layer — Zero-Knowledge Memory

Synapse Layer — Zero-Knowledge Memory

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synapselayer.orgMemory & Knowledge13Updated 6d ago

About Synapse Layer — Zero-Knowledge Memory

Synapse Layer is persistent, encrypted memory infrastructure for AI agents and assistants. Semantic recall and Trust Quotient scoring support continuity across sessions and MCP clients.

Key features

  1. 01AES-256-GCM encrypted storage
  2. 02Semantic recall across sessions
  3. 03Memory shared across agents
  4. 04Trust Quotient confidence scoring
  5. 0513 MCP tools

Use cases

  1. 01Retain user preferences and decisions between sessions
  2. 02Carry context between different agents
  3. 03Provide encrypted memory to MCP clients
  4. 04Search structured memory for production agents

MCP support

Exposes 13 memory tools over MCP JSON-RPC for compatible clients to store, search, and recall memories.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"synapselayer-synapse-secure-memory": {
"command": "uvx",
"args": [
"synapse-layer"
],
"env": {
"SYNAPSE_AGENT_ID": "<SYNAPSE_AGENT_ID>",
"SYNAPSE_PRIVACY_EPSILON": "<SYNAPSE_PRIVACY_EPSILON>",
"SYNAPSE_ENCRYPTION_KEY": "<SYNAPSE_ENCRYPTION_KEY>",
"LOG_LEVEL": "<LOG_LEVEL>"
}
}
}
}
Run commanduvx synapse-layer
Environment variables to set
SYNAPSE_AGENT_IDIdentifier for the agent using the memory layer (e.g., claude-desktop, my-agent).
SYNAPSE_PRIVACY_EPSILONDifferential privacy epsilon parameter. Lower values = stronger privacy. Range: 0.1–2.0.
SYNAPSE_ENCRYPTION_KEYSecretAES-256-GCM encryption key for at-rest memory encryption. Auto-generated if not provided.
LOG_LEVELLogging verbosity: DEBUG, INFO, WARNING, ERROR. Default: INFO.

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
pypisynapse-layer1.0.7

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

🧠 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.

PyPI Python Downloads MCP Compatible Official MCP Registry CI License: Apache-2.0 Smithery

Website · Docs · PyPI · Forge


⚡ 30-Second Quickstart

Get your Connect Token at forge.synapselayer.org → Connect, then install into any MCP client:

curl -fsSL https://forge.synapselayer.org/install/smithery | bash

On the Forge dashboard the Smithery card already copies the command with your token embedded (… | bash -s -- sk_connect_…) — a single paste in your terminal is enough.

Or use the Python SDK:

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.

FeatureDescription
🔐 Encrypted at restAES-256-GCM with per-operation random IV and HMAC-SHA-256 integrity
🧩 One-click connectClaude Desktop, Cursor, LangChain, CrewAI, n8n
🌐 Cross-agent memorySave in ChatGPT, recall in Claude
⚡ MCP-nativeAny MCP-compatible agent
🔒 Header-first authTokens never in URLs or logs
🎯 Trust QuotientDeterministic 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 LayerWith Synapse Layer
Agent forgets context every sessionPersistent memory across all sessions
Memory locked to one modelCross-agent: save in ChatGPT, recall in Claude
No audit trailTrust Quotient scoring on every memory
Complex integrationpip install synapse-layer + 3 lines of code
Plaintext stored on serversAES-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 (one tested path per client)

Claude Code (CLI)
claude mcp add --transport http synapse-layer \
  https://forge.synapselayer.org/api/mcp \
  --header "x-connect-token: sk_connect_YOUR_TOKEN"

The URL is a positional argument — claude mcp add --transport http <name> <url> — there is no --url flag.

Claude Desktop

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"
      ]
    }
  }
}
Cursor

Add to .cursor/mcp.json in your project root (same JSON block as above).

Any MCP client

Any host that runs npx can use the mcp-remote block above unchanged — it bridges local stdio to the remote endpoint.

Config file locations:

  • Claude Desktop — macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Claude Desktop — Windows: %APPDATA%\Claude\claude_desktop_config.json
  • Claude Desktop — 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

FeatureImplementation
EncryptionAES-256-GCM at rest with per-operation random IV
IntegrityHMAC-SHA-256 on content
AuthHeader-first (x-connect-token) — tokens never in URLs or logs
PrivacyContent sanitization + tenant-scoped encrypted storage
Isolation1 user = 1 tenant = 1 private mind

See SECURITY.md for vulnerability reporting.


Related Projects

ProjectDescription
synapse-sdk-pythonPython SDK — LangChain, CrewAI, and A2A protocol adapters
synapse-layer-skillMCP skill configuration for Claude Desktop, Cursor, Windsurf
synapse-layer-langgraphLangGraph 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

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.