Find relevant documentation information using natural language queries. Search across stored documentation sources to locate specific details, code examples, or related content with ranked results.
Find relevant information across stored documentation using natural language queries. Returns ranked excerpts with context for specific details, code examples, or related documentation.
Identify related documentation files by analyzing metadata from a specified project path and document file to enhance knowledge retrieval and organization.
Rename a document within the MCP Documentation Service without altering its content or location. Optionally updates references to the document in related files for consistency.
A Model Context Protocol server that enables intelligent searching across documentation for 30+ programming libraries and frameworks, fetching relevant information from official sources.
Efficiently delivers project documentation to AI agents like Claude on-demand, optimizing token usage by loading context only when needed. Supports document retrieval, listing, and keyword search with security features.
Enables document-based question answering using OpenAI's GPT-4 with semantic search and embeddings. Upload PDF, TXT, or Markdown files and get answers strictly based on document content with source attribution and confidence scores.