This is a lightweight vector search implementation that runs in memory and uses TF-IDF with cosine similarity for document matching. The repository doesn't expose much documentation, but the core use case is clear: you need semantic search without external dependencies or heavy embedding models. It's designed to work with x402 micropayments, suggesting a pay-per-query model running on the remote endpoint at klymax402.com. Reach for this when you want basic similarity search for Claude without spinning up a vector database or paying for OpenAI embeddings. The tradeoff is simplicity over sophistication, TF-IDF won't understand semantic meaning the way transformers do, but it's fast and deterministic for keyword-adjacent matching.
In-memory vector store with TF-IDF vectorization and cosine similarity search. Pay-per-call via x402 (USDC on Base L2) -- no API key, no signup, no rate-limit wall.
Part of the klymax402 marketplace -- 100 x402 micropayment APIs for AI agents, one wallet, USDC on Base.
Add to your MCP client config (Claude Desktop, Cursor, ElizaOS, etc.):
{
"mcpServers": {
"vector-search": {
"url": "https://vector-search.api.klymax402.com/mcp"
}
}
}
curl -X POST "https://vector-search.api.klymax402.com/api/search" \
-H "Content-Type: application/json" \
-d '{"query":"..."}'
# -> 402 Payment Required, with an x402 payment challenge in the response body
Any x402-aware client (@x402/fetch, x402-agent-tools, ATXP) handles the 402 -> sign -> retry cycle automatically.
| Tool | Method | Path | Price | Description |
|---|---|---|---|---|
data_vector_search | POST | /api/search | $0.005 | Store text and search by semantic similarity |
data_vector_searchUse 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 most relevant matches. Returns top-k results with similarity scores. Do NOT use for web search — use web_search_query instead. Do NOT use for keyword research — use keyword_research instead. Do NOT use for text classification — use text_classify instead.
Parameters
| Name | Type | Required | Description |
|---|---|---|---|
documents | array | no | Array of text documents to index (optional if already stored in this session) |
query | string | yes | The text query to search for |
topK | number | no | Number of top results to return (default: 3, max: 10) |
namespace | string | no | Namespace to isolate document sets (default: 'default') |
eip155:8453)100 x402 micropayment APIs for AI agents -- one wallet, USDC on Base, zero signup.
MIT
io.github.ericm1018/skillfm-llm-cost-optimizer-openai-anthropic-usage
io.github.mikerawsonnz/llm-orchestration-agent
io.github.mikerawsonnz/authenticated-llm-agent
labforgedev/copilot-memory-mcp
csoai-org/agent-prompt-injection-firewall-mcp
io.github.mikerawsonnz/authenticated-multi-llm-agent