AskDocs
Facilitates RAG-powered semantic search across technical documentation PDFs leveraging Ollama.
About
AskDocs provides a Model Context Protocol (MCP) server designed for intelligent search over your technical documentation. It allows users to perform semantic searches using natural language queries across multiple PDF documents, complete with precise page citations. The server supports Docker for easy deployment and persistent caching of vector stores, and offers flexible TOML-based configuration for documents and models. By integrating with AI-powered development environments like Cursor and Codex, AskDocs enables developers to quickly find relevant information within their project documentation, significantly enhancing productivity and knowledge retrieval.
Key Features
- Supports multiple PDF documents with page citations
- Flexible TOML-based configuration
- Provides a Model Context Protocol (MCP) server for AI tool integration
- 0 GitHub stars
- Semantic search with natural language queries
- Docker support with persistent caching for vector stores
Use Cases
- Enhance developer productivity by providing semantic search directly within IDEs like Cursor and Codex.
- Create intelligent, searchable knowledge bases from diverse PDF-based technical manuals.
- Facilitate quick access to document sections with precise page citations for specific queries.
