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Vector Search — In-Memory TF-IDF Semantic Store vs WhenLabs-org/when

Side-by-side comparison of two Model Context Protocol servers. Pick the right one for Claude Desktop, Claude Code, or Cursor.

In-memory vector search API for AI agents. Store documents and query by semantic meaning using TF-IDF vectorization with cosine similarity. Lightweight…

Details

Developer toolkit: auto-detect stack for AI context files, catch port conflicts, validate .env schemas, spot docs drift, audit dependency licenses, and time cod

Details

Comparison

FeatureVector Search — In-Memory TF-IDF Semantic StoreWhenLabs-org/when
PricingFreeFree
Installs
Rating
Verified
HostedHosted
Tools
Categoryproductivityproductivity
Authoraxel-belfortWhenLabs-org
RepoWhenLabs-org/when

When to pick Vector Search — In-Memory TF-IDF Semantic Store

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.

When to pick WhenLabs-org/when

Developer toolkit: auto-detect stack for AI context files, catch port conflicts, validate .env schemas, spot docs drift, audit dependency licenses, and time coding tasks — 7 MCP tools, one install.

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