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Ismael Marchi
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docs: launch narrative - focus on demonstration over explanation
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‎README.md‎

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<div align="center">
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# Synapse Layer
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# Synapse Layer — Long-Term Memory for AI Agents
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### Autonomous Memory Engine for AI Agents
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**Infinite Memory. Zero Context Loss. Built-in Security.**
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<br>
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*The open-core memory standard for the next generation of AI agency.*
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> **Plug once. Remember forever. Zero-Knowledge. Zero-Amnesia. 🧠**
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<br>
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[![Documentation](https://img.shields.io/badge/Docs-Mintlify-0D9373)](https://docs.synapselayer.org)
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[![v1.0.7 Stable](https://img.shields.io/badge/v1.0.7-stable-informational)](CHANGELOG.md)
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[Website](https://synapselayer.org) · [Forge](https://forge.synapselayer.org) · [Docs](https://forge.synapselayer.org/docs) · [PyPI](https://pypi.org/project/synapse-layer/) · [Smithery](https://smithery.ai/servers/synapselayer/synapse-protocol)
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[Website](https://synapselayer.org) · [Forge](https://forge.synapselayer.org) · [Docs](https://docs.synapselayer.org) · [PyPI](https://pypi.org/project/synapse-layer/) · [Smithery](https://smithery.ai/servers/synapselayer/synapse-protocol)
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<!-- mcp-name: io.github.SynapseLayer/synapse-secure-memory -->
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</div>
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---
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```python
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from synapse_layer import SynapseMemory
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memory = SynapseMemory(agent_id="my-agent")
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# 1. Agents save context automatically
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memory.save("User prefers absolute security and neural handover.")
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# 2. Recall is deterministic and explainable
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info = memory.recall("user focus")
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# Result: "User prefers absolute security and neural handover."
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```
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That's the entire API. **Encryption, PII redaction, differential privacy, intent validation, and trust scoring** — all happen under the hood. No configuration. No boilerplate. No amnesia.
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---
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## 🚀 Quick Install
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**Via Smithery (recommended for MCP agents):**
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<div align="center">
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<strong>Giving Agents a Past. Giving Models a Soul. ⚗️</strong>
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<br><br>
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<a href="https://synapselayer.org">Website</a> · <a href="https://forge.synapselayer.org">Forge</a> · <a href="https://forge.synapselayer.org/docs">Docs</a> · <a href="https://github.com/SynapseLayer/synapse-layer">GitHub</a> · <a href="https://pypi.org/project/synapse-layer/">PyPI</a> · <a href="https://smithery.ai/servers/synapselayer/synapse-protocol">Smithery</a>
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<a href="https://synapselayer.org">Website</a> · <a href="https://forge.synapselayer.org">Forge</a> · <a href="https://docs.synapselayer.org">Docs</a> · <a href="https://github.com/SynapseLayer/synapse-layer">GitHub</a> · <a href="https://pypi.org/project/synapse-layer/">PyPI</a> · <a href="https://smithery.ai/servers/synapselayer/synapse-protocol">Smithery</a>
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<br><br>
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Built by <a href="https://forge.synapselayer.org">Ismael Marchi</a> · <a href="https://x.com/synapselayer">@synapselayer</a>
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</div>

‎docs/introduction.mdx‎

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---
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title: Introduction
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description: "Infinite Memory. Zero Context Loss. Built-in Security."
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description: "Plug once. Remember forever. Zero-Knowledge. Zero-Amnesia."
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---
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# Synapse Layer
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# Synapse Layer — Long-Term Memory for AI Agents
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**The autonomous memory engine for AI agents.**
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> Plug once. Remember forever. Zero-Knowledge. Zero-Amnesia. 🧠
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Synapse Layer solves the fundamental problem of **agent amnesia** — AI agents forget everything between sessions, waste tokens re-asking questions, and lose critical context when switching models.
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```python
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from synapse_layer import SynapseMemory
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With Synapse Layer, your agents get:
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memory = SynapseMemory(agent_id="my-agent")
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- **Persistent memory** that survives across sessions
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- **Built-in security** — PII/secrets redacted before storage
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- **Autonomous detection** — milestones, decisions, and alerts saved automatically
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- **Cross-model transfer** — context moves between GPT-4, Claude, and others via Neural Handover™
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- **Deterministic recall** — every result is explainable, ranked by Trust Quotient™
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# 1. Agents save context automatically
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memory.save("User prefers absolute security and neural handover.")
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# 2. Recall is deterministic and explainable
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info = memory.recall("user focus")
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# Result: "User prefers absolute security and neural handover."
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```
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That's the entire API. **Encryption, PII redaction, differential privacy, intent validation, and trust scoring** — all happen under the hood. No configuration. No boilerplate. No amnesia.
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Synapse Layer solves the fundamental problem of **agent amnesia** — AI agents forget everything between sessions, waste tokens re-asking questions, and lose critical context when switching models.
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<CardGroup cols={2}>
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<Card title="Quick Start" icon="rocket" href="/docs/quickstart">
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<Card title="Quick Start" icon="rocket" href="https://docs.synapselayer.org/docs/quickstart">
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Install via Smithery, PyPI, or direct MCP connection in under 60 seconds.
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</Card>
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<Card title="Architecture" icon="brain" href="/docs/architecture">
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<Card title="Architecture" icon="brain" href="https://docs.synapselayer.org/docs/architecture">
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Understand the TQ Intelligence pipeline and how memory flows through the system.
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</Card>
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<Card title="Security" icon="shield-halved" href="/docs/security">
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<Card title="Security" icon="shield-halved" href="https://docs.synapselayer.org/docs/security">
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Zero-Leak Policy: 15+ patterns protect PII and secrets before any I/O.
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</Card>
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<Card title="MCP Server" icon="plug" href="/docs/mcp-server">
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<Card title="MCP Server" icon="plug" href="https://docs.synapselayer.org/docs/mcp-server">
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4 tools ready for Claude Desktop, LangChain, CrewAI, and custom agents.
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</Card>
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</CardGroup>
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| Black-box recall ranking | Trust Quotient™ — deterministic, explainable scoring |
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| Manual tagging required | Auto-Save Engine detects what matters autonomously |
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## The A-ha Moment
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```python
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from synapse_layer import SynapseMemory
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import asyncio
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async def main():
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mem = SynapseMemory(agent_id="my-agent")
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# Store — PII redacted, encrypted, privacy-noised automatically
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await mem.store("User prefers dark mode", confidence=0.95)
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# Recall — ranked by Trust Quotient™, self-healing on conflicts
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results = await mem.recall("user preferences")
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for r in results:
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print(f"{r.content} (TQ: {r.trust_quotient:.3f})")
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asyncio.run(main())
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```
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That’s it. Encryption, sanitization, differential privacy, intent validation, and trust scoring — all happen under the hood.
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<Note>
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Synapse Layer follows an **open-core model**. The SDK, MCP server, and security pipeline are fully open source (Apache 2.0). Advanced scoring and intelligence are available via the PRO tier.
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</Note>
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</Note>

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