Synapse Layer — Trust Infrastructure for AI Agents

io.github.SynapseLayer由 GitHub 帳號 SynapseLayer 發布v2.4.6更新於 Oct 24, 2026

MCP-native Trust Infrastructure for AI Agents. Persistent encrypted memory with Trust Quotient.

已驗證Streamable HTTP可網頁執行知識與記憶AI 與機器學習

概覽

AI 產生的概覽

遠端 MCP 記憶服務,讓助理跨工作階段、跨代理儲存、搜尋並召回持久化的加密記憶。

可以做什麼
  • 儲存與寫入記憶,包含附中繼資料與信任評分的結構化條目,以及從自由文字中擷取候選記憶
  • 依語意、時間、優先順序或混合路由及全文比對召回與搜尋已存記憶,並提供同義工具別名
  • 為工作階段初始化持久記憶脈絡,並分頁列出記憶中繼資料
  • 提交回饋以調整記憶的信任評分,並在代理之間交接脈絡狀態
  • 檢查服務可用性,取得運作時間與 SLO 指標
適用情境
適合需要助理在工作階段之間記住使用者偏好、事實與先前決策的情境,也適合多個 MCP 用戶端與代理共用同一受治理記憶庫的情況。團隊若需要具信任評分、可搜尋的生產代理運作記憶,也可考慮。
執行需求
需要連線至 forge.synapselayer.org 的遠端端點(streamable HTTP),不必在本機安裝套件;不支援原生 HTTP 的用戶端可透過 npx mcp-remote 橋接。需要從 Forge 主控台取得的 Connect 權杖(sk_connect_ 前綴),以 x-connect-token 標頭傳送。需要網路連線。
安裝前請注意
x-connect-token 標頭是存取記憶庫的機密憑證,應避免寫入共用設定或日誌。記憶內容會上傳並保存在第三方服務,不宜存入敏感的个人或商業資料。多個工具會寫入、修改或匯出資料,部分召回與匯出呼叫需填寫理由並受速率限制。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Synapse Layer — Trust Infrastructure for AI Agents,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/io.github.SynapseLayer%2Fsynapse-layer/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。

{
  "mcpServers": {
    "synapse-layer-trust-infrastructure-for-a": {
      "type": "http",
      "url": "https://forge.synapselayer.org/api/mcp"
    }
  }
}

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:

bash
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:

python
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

bash
pip install synapse-layer

Quick Start

Python Script

python
from synapse_layer import Synapse
client = Synapse(token="sk_connect_YOUR_TOKEN")
# Storeclient.store("User prefers dark mode and concise answers")
# Recallresults = client.recall("user preferences")for r in results:    print(r["content"], r["trust_quotient"])

With Context Manager

python
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)

bash
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:

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

bash
# Health checkcurl -H "x-connect-token: sk_connect_YOUR_TOKEN" \  https://forge.synapselayer.org/api/connect/health
# Save memorycurl -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

來源:README.md,提交 96d0706

工具

13

recall

Recall Memory

Retrieve relevant persisted memory using semantic, temporal, priority, or hybrid routing. Governance: requires reason (10–200 chars). Rate limit: 20/min.

輸入參數modelimitquery必填scopereason必填subjectagent_id

save_to_synapse

Save to Synapse

Persist memory with encryption at rest, sanitization, and deduplication controls.

輸入參數tagstypecontent必填projectsubjectagent_idimportanceforce_intentintent_reason

process_text

Process Text

Extract candidate memories from free-form text with governance filters and sanitization.

輸入參數text必填sourceprojectagent_id

health_check

Health Check

Check service availability, engine version, and storage health. Public method.

無需輸入參數。

initialize_context

Initialize Context

Initialize a persistent memory context for a conversation or agent session. Returns REDACTED metadata by default (detail="summary"). Use detail="full" with a reason (10–200 chars) to retrieve plaintext content under MEMORY_EXPORT_GOVERNANCE_V1.

輸入參數detailreason

save_memory

Save Memory

Save a memory entry to the persistent store. Alias of save_to_synapse.

輸入參數tagscontent必填subjectagent_idforce_intentintent_reason

store_memory

Store Memory

Store structured memory with metadata and trust scoring.

輸入參數tagscontent必填subjectagent_idforce_intentintent_reason

recall_memory

Recall Memory

Recall persisted memory by query. Alias of recall.

輸入參數modelimitquery必填scopereason必填subjectagent_id

list_memories

List Memories

List memory metadata with pagination and governance limits.

輸入參數limitscopesubjectagent_id

memory_feedback

Memory Feedback

Submit feedback to adjust trust scoring for stored memories.

輸入參數signal必填memoryIdmemory_idsessionIdsession_id

neural_handover

Neural Handover

Transfer contextual state between agents with continuity controls.

輸入參數token必填reason必填consuming_agent

slo_report

SLO Report

Return uptime and SLO metrics for the MCP service.

輸入參數admin_token必填window_hours

版本歷史

1
  1. v2.4.6最新Sep 16, 2026

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