Knowledge Raven: A Model-Agnostic Knowledge Base Platform Built with Claude Code
Knowledge Raven is a knowledge base platform that enables any MCP-compatible LLM (Claude, GPT, etc.) to search company documents and retrieve specific sections with source citations. The platform functions as structured, permission-aware memory for AI assistants.
Platform Features and Capabilities
The platform supports document uploads and connections to various sources including Drive, Confluence, Notion, Dropbox, and GitHub. It offers a free tier with limits of 50 documents and 3 users.
Technical Architecture
The entire platform was built using Claude Code by a solo founder. The technical stack includes:
- Backend: Python/FastAPI
- MCP tool layer
- Agentic RAG pipeline with parent-child retrieval
- Contextual embeddings
- Hybrid search
Inspiration and Context
The development was inspired by Andrej Karpathy's workflow for building personal knowledge bases with LLMs, which involves compiling raw sources into structured wikis and querying them with agents. Karpathy noted his approach works well at small scale (~100 articles, ~400K words) but acknowledged limitations for larger implementations, stating: "I think there is room here for an incredible new product instead of a hacky collection of scripts."
Knowledge Raven addresses this gap by scaling to enterprise needs, handling 50,000+ pages with access controls and live-synced sources. The platform implements actual agentic RAG infrastructure, which becomes necessary at this scale compared to simpler script-based approaches.
Technical Approach and Philosophy
The developer clarifies that Karpathy's system is tool-based, where the LLM operates on external files, calls a search engine as a tool, and writes structured output. This aligns with the MCP pattern used by Knowledge Raven. The post addresses misconceptions about fine-tuning, noting that fine-tuning enterprise knowledge into model weights would lose source attribution, permissions, and real-time update capabilities.
The developer built Knowledge Raven specifically to solve the problem of giving AI assistants access to organizational knowledge bases at team scale, moving beyond individual workflows to enterprise-ready solutions.
📖 Read the full source: r/ClaudeAI
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