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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.
--- 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.--- 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.
Includes the original skill and its supporting files. Review scripts and install any external dependencies before use.