Synapse Layer — Continuous Consciousness Infrastructure MCP Server

Persistent zero-knowledge memory for AI agents. AES-256-GCM encryption, PII redaction.

Local serverstdioPython

What is the Synapse Layer — Continuous Consciousness Infrastructure MCP server?

Synapse Layer — Continuous Consciousness Infrastructure MCP server is a locally run integration for AI assistants that speak the Model Context Protocol. Persistent zero-knowledge memory for AI agents. AES-256-GCM encryption, PII redaction.

What you get

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.

The persistent memory layer for AI agents — the missing piece between stateless LLMs and real continuity of context.

Setting it up

The server ships on PyPI as synapse-layer, so your MCP client can launch it on demand — there is no separate build step. Add the server block to your client's configuration, restart it, and the tools register themselves.

What the assistant can call

Once Synapse Layer — Continuous Consciousness Infrastructure is connected, these are the calls the assistant has available:

  • recall — save_to_synapse
  • process_text — search
  • health_check — initialize_context
  • save_memory — store_memory
  • recall_memory — list_memories
  • memory_feedback — neural_handover
  • multi — agent systems
  • MCP — based integrations

Before you rely on it

  • It runs with your machine's permissions. That is convenient and also the reason to think about what you point it at before you approve a tool call.
  • MCP clients confirm each tool call by default. Leave that on until you have watched what the synapse layer — continuous consciousness infrastructure mcp server does with a few real requests.

Choosing this one

Plenty of knowledge and memory servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call. Synapse Layer — Continuous Consciousness Infrastructure's toolset — recall, process_text, health_check and 5 more — is a fair guide to whether it matches your workflow. It is maintained by SynapseLayer; worth a glance at recent repository activity before you build anything load-bearing on it.

We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.

Available tools

ToolWhat it does
recallsave_to_synapse
process_textsearch
health_checkinitialize_context
save_memorystore_memory
recall_memorylist_memories
memory_feedbackneural_handover
multiagent systems
MCPbased integrations

How to install the Synapse Layer — Continuous Consciousness Infrastructure MCP server

{
  "mcpServers": {
    "synapse-layer": {
      "command": "uvx",
      "args": ["synapse-layer"]
    }
  }
}

Add to claude_desktop_config.json, then restart Claude Desktop.

Example prompts to try

  • Use Synapse Layer — Continuous Consciousness Infrastructure to recall.
  • Use Synapse Layer — Continuous Consciousness Infrastructure to process text.
  • Use Synapse Layer — Continuous Consciousness Infrastructure to health check.

Frequently asked questions

It connects Synapse Layer — Continuous Consciousness Infrastructure to MCP-compatible AI assistants such as Claude and Cursor, exposing 8 tools (recall, process_text, health_check, and more) that the assistant can call on your behalf. Instead of copying data back and forth by hand, the assistant works with Synapse Layer — Continuous Consciousness Infrastructure directly.