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112,291 tools. Last updated 2026-04-20 11:07
  • 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.
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  • Perform semantic search using vector embeddings with FAISS acceleration for better conceptual matching.
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  • 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.
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  • 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.
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