Generate vector embeddings for text search and similarity comparison.

Find ENS names semantically similar to a given name using vector embeddings across 3.6M+ names. Returns similar names with similarity scores and live marketplace data (price, owner, expiry). Great for discovering related names for portfolio building or brand exploration.

AgentPMT Tool Search and Execution - Unified interface for discovering, searching, and using AgentPMT tools without MCP refresh. Access tools required for workflows and skills here.

Perform semantic search using vector embeddings with FAISS acceleration for better conceptual matching.

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.