Kit for AI

About Kit for AI

Kit for AI is a memory and knowledge layer for agents that ships as native MCP tools, so the agent calls it directly rather than going through an application you have to build. The argument it makes is that most teams end up assembling the same retrieval stack — a vector database, a parser, an embedding pipeline, a chunking strategy and something to keep it all in sync — and then maintaining it forever, when what they actually wanted was for the model to remember things and be able to cite documents. So the product covers both halves. On the ingestion side it converts documents of essentially any format into model-ready text: PDFs and office files, URLs and web pages into clean Markdown, OCR for scans and images, YouTube videos into searchable notes, and JSON extraction that returns structured data shaped to a schema you define. On the retrieval side it maintains persistent knowledge bases the agent can search and cite, so answers are grounded in your own documents rather than in whatever the model absorbed during training. It is model-agnostic by design — the site lists OpenAI, Claude, Gemini, Llama, Mistral, Perplexity, DeepSeek, Cohere, Grok and Qwen — and there is a playground plus documentation covering auth, data handling and limits. The free tier runs without a card.

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