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Vector Search x402

Vector Search x402

Remote
github.comMemory & Knowledge0Updated 8w ago

About Vector Search x402

Vector Search x402 is an in-memory text vector store for AI agents building RAG pipelines. It uses TF-IDF and cosine similarity, with searches paid per call in USDC on Base.

Key features

  1. 01In-memory text document storage
  2. 02TF-IDF vectorization
  3. 03Cosine similarity ranking
  4. 04Top-k results with scores
  5. 05Namespace-based document separation
  6. 06Pay-per-call with USDC on Base

Use cases

  1. 01Search stored text for relevant passages
  2. 02Retrieve context for a RAG pipeline

MCP support

An MCP endpoint exposes the data_vector_search tool to MCP clients. It accepts documents and a query, then returns ranked matches.

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://vector-search.api.klymax402.com/mcp
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

Tools

Details

From the project README

Vector Search API

MCP Server x402 License: MIT

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.

Quickstart -- MCP

Add to your MCP client config (Claude Desktop, Cursor, ElizaOS, etc.):

{
  "mcpServers": {
    "vector-search": {
      "url": "https://vector-search.api.klymax402.com/mcp"
    }
  }
}

Quickstart -- HTTP (x402)

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.

Tools

ToolMethodPathPriceDescription
data_vector_searchPOST/api/search$0.012Store text and search by semantic similarity
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 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

NameTypeRequiredDescription
documentsarraynoArray of text documents to index (optional if already stored in this session)
querystringyesThe text query to search for
topKnumbernoNumber of top results to return (default: 3, max: 10)
namespacestringnoNamespace to isolate document sets (default: 'default')

Example agent prompts

  • "Store text documents and search them by semantic similarity"

Payment

  • Protocol: x402 -- HTTP-native pay-per-call, no signup, no API key
  • Network: Base L2 (eip155:8453)
  • Asset: USDC
  • Facilitator: Coinbase CDP (primary), PayAI (fallback)

Part of klymax402

100 x402 micropayment APIs for AI agents -- one wallet, USDC on Base, zero signup.

License

MIT

Comments

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