synapse-layer/smithery.yaml at main · SynapseLayer/synapse-layer · GitHub

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qualifiedName: "@synapselayer/synapse-protocol"
displayName: "Synapse Layer"
description: >
  Persistent memory infrastructure for AI agents — encrypted,
  governed, and cross-agent. State Continuity Layer.
version: "2.3.3"
icon: "🧠"
sourceUrl: "https://github.com/SynapseLayer/synapse-layer"
homepage: "https://synapselayer.org"
license: "Apache-2.0"
author:
  name: "Ismael Marchi"
  url: "https://synapselayer.org"

serverUrl: "https://forge.synapselayer.org/api/mcp"
startCommand:
  type: "http"
  url: "https://forge.synapselayer.org/api/mcp"
  httpHeaders:
    x-connect-token: "{{config.connect_token}}"

configSchema:
  type: "object"
  required:
    - connect_token
  properties:
    connect_token:
      type: "string"
      description: "Your Synapse Connect Token. Get it at synapselayer.org → Dashboard → Connect."
    agent_id:
      type: "string"
      description: "Identifier for the agent using the memory layer. Defaults to 'default'."
      default: "default"

tools:
  - name: recall
    description: "Retrieves relevant past context and decisions to maintain continuity across interactions."
    inputSchema:
      type: object
      required: [query]
      properties:
        query:
          type: string
          description: "What to recall from memory"
        agent_id:
          type: string
          description: "Agent identifier to scope recall. Defaults to 'default'."
        limit:
          type: number
          description: "Maximum memories to return (1-50, default: 10)"

  - name: save_to_synapse
    description: "Stores structured memory securely using AES-256-GCM encryption. Server never sees plaintext."
    inputSchema:
      type: object
      required: [content]
      properties:
        content:
          type: string
          description: "Content to persist in encrypted memory"
        agent_id:
          type: string
          description: "Agent identifier. Defaults to 'default'."

  - name: process_text
    description: "Extracts and persists structured memory from text input to maintain long-term context."
    inputSchema:
      type: object
      required: [text]
      properties:
        text:
          type: string
          description: "Text to process and extract memories from"
        agent_id:
          type: string
          description: "Agent identifier. Defaults to 'default'."

  - name: search
    description: "Searches across stored memory using semantic retrieval. Returns results ranked by relevance and confidence."
    inputSchema:
      type: object
      required: [query]
      properties:
        query:
          type: string
          description: "Search query — natural language or keywords"
        agent_id:
          type: string
          description: "Optional agent filter. Omit to search across all agents."
        limit:
          type: number
          description: "Maximum results to return (1-50, default: 20)"

  - name: health_check
    description: "Verify system availability and memory pipeline integrity."
    inputSchema:
      type: object
      properties: {}

tags:
  - agent-memory
  - persistent-context
  - long-term-memory
  - mcp-memory
  - aes-256-gcm
  - pii-redaction
  - mcp
  - ai-agents
  - langchain
  - crewai
  - autogen
  - llamaindex
  - semantic-kernel
  - privacy
  - encryption
  - cross-agent
  - state-continuity