{"repo":"mshtawythug/second-brain","free":true,"listed":false,"github":"https://github.com/mshtawythug/second-brain","clone":"git clone https://github.com/mshtawythug/second-brain.git","description":"Local-first personal knowledge base CLI — hybrid FTS + pgvector search, a GraphRAG entity graph, and LLM enrichment over your notes, transcripts, Slack & Gmail. Runs fully local on Ollama (no cloud, no API keys); queryable by any AI agent through the built-in MCP server. Postgres-backed, publishes an Obsidian-style Quartz wiki.","language":"Python","stars":12,"topics":["cli","embeddings","graphrag","hybrid-search","knowledge-base","local-ai","local-first","mcp","mcp-server","note-taking"],"license":"MIT","category":"mcp-servers","readme_excerpt":"Second Brain Local, queryable knowledge base and note vault with hybrid search and an entity-graph layer — searchable by any AI coding agent or assistant from any conversation. Stores career docs, interview prep, Krisp transcripts, Slack threads, Gmail, and authored Markdown notes in Postgres + pgvector. Any agent reaches all of it through the brain CLI or the bundled brain-mcp MCP server — no re-pasting context into every chat. You get the same corpus through the CLI, a local web UI, or a rendered wiki. The everyday loop — capture a note, search it back, read the top hit, check the corpus: Token savings Querying brain returns a ranked snippet instead of dumping whole threads and files into an agent's context, so a lookup costs a fraction of the tokens a direct MCP or file read would: Source Direct read (MCP / Read tool) Via brain (search + optional show ) Savings --- --- --- --- Gmail thread 15–50k (metadata + full threads with quoted replies / headers) 2–4k (snippets + one targeted brain show ) 5–15× Krisp transcript 25–75k (search + full transcripts across candidates) 6–16k (search + one relevant transcript) 4–10× Long PDF / DOCX (30+ pages) 15–25k (read the whole file) 1–9k (one snippet + targeted show ) 5–15× Brain stores pre-extracted, quote-stripped bodies and hybrid-ranks before fetching, so only the passage that matched enters context. See the full per-source breakdown. When the reader is an agent rather than a person, brain recall goes one step further. Instead of a","default_branch":null,"files":null,"tree":[],"storefront":"/r/mshtawythug","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/mshtawythug/second-brain/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}