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Surfsense

Air-gapped, privacy-focused AI research assistant and NotebookLM alternative (MODSetter/SurfSense). Use when the agent needs to index, research, transform, and synthesize local documentation, codebase notes, whitepapers, or research data without leaking privacy to external cloud servers.

Installable skillMITBy smartworldarafathUpdated Nov 11, 2026
INTENDED FORInstall in a listed agent.

instructions.md

---
name: surfsense
description: Air-gapped, privacy-focused AI research assistant and NotebookLM alternative (MODSetter/SurfSense). Use when the agent needs to index, research, transform, and synthesize local documentation, codebase notes, whitepapers, or research data without leaking privacy to external cloud servers.
---

# SurfSense (Privacy-Focused Research & Document Intelligence)

Based on [MODSetter/SurfSense](https://github.com/MODSetter/SurfSense): an air-gapped, privacy-first, open-source NotebookLM alternative. It enables AI agents to research, transform, query, and edit extensive document collections, source notes, and technical literature completely offline or with private LLMs.

---

## 🎯 When to Use
- **Deep Document Research:** Synthesizing architectural patterns, API documentation, and reverse-engineering research notes across large repositories.
- **Air-Gapped / Private Analysis:** Querying sensitive proprietary specifications, leaked source archives, or internal security reports without external cloud exposure.
- **Multi-Source Knowledge Synthesis:** Blending Markdown notes, PDFs, web bookmarks, and transcripts into unified, cited technical summaries.

---

## 🚀 Setup & Execution

### 1. Local / Self-Hosted Setup
SurfSense can run entirely locally with Docker or Python:

```bash
# Clone the SurfSense repository
git clone https://github.com/MODSetter/SurfSense.git
cd SurfSense

# Quickstart via Docker Compose
docker compose up -d
```

### 2. Pairing with Local LLMs (Ollama / LM Studio)
Configure SurfSense to point to local Ollama endpoints for 100% offline document intelligence:
- Base URL: `http://localhost:11434/v1`
- Embedding Model: `nomic-embed-text` or `bge-m3`
- Reasoning Model: `llama3.3`, `qwen2.5-coder`, or `deepseek-r1`

---

## ⚡ Integration with REA & Security Workflows
1. **Disassembly & Decompiler Notes RAG:** When reverse-engineering large binaries with REA, index Ghidra/Hopper decompiled dumps into SurfSense to perform semantic search across millions of lines of recovered pseudocode.
2. **Vulnerability Case Knowledge Base:** Keep a private local repository of past audit reports, CVE advisories, and security notes that can be queried during website security assessments.
3. **Zero Data Leakage:** Ensure proprietary client code or unpublished app data is never indexed in third-party hosted vector stores.

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