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In-memory vector search API for AI agents. Store documents and query by semantic meaning using TF-IDF vectorization with cosine similarity. Lightweight alternat
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.
Run in your terminal:
claude mcp add vector-search -- npx -y @smithery/cli run axel-belfort/vector-searchYes, Vector Search — In-Memory TF-IDF Semantic Store MCP is free — one-click install via Unyly at no cost.
No, Vector Search — In-Memory TF-IDF Semantic Store runs without API keys or environment variables.
Self-hosted: the server runs locally on your machine via the install command above.
Open Vector Search — In-Memory TF-IDF Semantic Store on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.
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