Building RagRabbit, An Open Source RAG Search with Postgres as the Vector Store
Blog post from Neon
Marco D'Alia, a software architect behind RagRabbit, built the tool to simplify his own workflow by combining multiple systems for web scraping, vector search, and AI responses into one single, open-source toolkit. RagRabbit crawls websites, converts pages to Markdown, generates embeddings with Postgres via pgVector, provides AI Q&A using OpenAI or Claude, and offers an MCP server for read-only doc chunks directly into IDEs or chat apps. The tool accommodates different authentication setups, including user/password, GitHub OAuth, and magic links, and can be deployed on Vercel's Neon with a single click, taking advantage of its serverless scaling and Postgres features like full-text search.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| Vector Search | 14 | 2,157 | 323 | 132 | +11% |
| LLM | 9 | 5,694 | 663 | 215 | +42% |
| RAG | 5 | 1,706 | 255 | 85 | +12% |
| MCP | 4 | 2,270 | 107 | 59 | +770% |
| Serverless | 3 | 826 | 205 | 95 | +45% |
| AI Model Fine-tuning | 1 | 889 | 213 | 97 | +38% |
Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.