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Vector Search — In-Memory TF-IDF Semantic Store

Search & Web Remote 1 tool

In-memory vector search API for AI agents. Store documents and query by semantic meaning using TF-IDF vectorization with cosine similarity. Lightweight alternative to Pinecone/Weaviate for small datasets. Tools: data_vector_search. Use this for building simple RAG systems, document matching, or semantic search over small collections (< 10K docs). IMPORTANT: For web-wide search, use web_search_query instead. Returns: {results[], scores[], matchCount}. No API key required — x402 micropayment $0.005/call on Base L2.

GitHub ↗ Docs ↗

How to connect

1
Add the remote MCP URL
Paste this endpoint into Claude, ChatGPT, or Cursor MCP settings.
https://vector-search--axel-belfort.run.tools
2
Verify the tools loaded
Confirm tools/list returns the expected tools before relying on them in production.

Tools

(1)
  • data_vector_search

    Use this when you need to store text documents and search them by semantic similarity. Accepts documents to store and a query to search. Uses TF-IDF vectorization with cosine similarity to find the mo

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