Use this tool to split long text into smaller, overlapping chunks suitable for embedding, vector storage, or RAG pipelines. Triggers: 'chunk this document for RAG', 'split this into embeddings', 'break this into segments', 'prepare this text for a vector database'. Returns an array of chunks with index, text, character count, and estimated token count. Essential before embedding or storing text in a vector database.
Use this tool to split long text into smaller, overlapping chunks suitable for embedding, vector storage, or RAG pipelines. Triggers: 'chunk this document for RAG', 'split this into embeddings', 'break this into segments', 'prepare this text for a vector database'. Returns an array of chunks with index, text, character count, and estimated token count. Essential before embedding or storing text in a vector database.
Lookup WHOIS information for an Autonomous System (AS) number from the RADB routing database. Returns routing policy, network information, and administrative contacts.
Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.
Enables AI applications to access and contextualize organizational knowledge sources including GitHub repositories and internal documentation through standardized MCP protocol integration. Features OAuth 2.1 authentication, vector-based semantic search, and optimized context chunking for enterprise development workflows.