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In-memory vector search with TF-IDF and cosine similarity. x402 micropayment.
About
In-memory vector search with TF-IDF and cosine similarity. x402 micropayment.
Remote endpoints: sse: https://vector-search.api.klymax402.com/mcp
Security Report
Valid MCP server (1 strong, 0 medium validity signals). No known CVEs in dependencies. Imported from the Official MCP Registry. Trust signals: trusted author (184/189 approved).
1 tool verified · Open access · No issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Required
This plugin requests these system permissions. Most are normal for its category.
How to Connect
Remote Plugin
No local installation needed. Your AI client connects to the remote endpoint directly.
Add this to your MCP configuration to connect:
{
"mcpServers": {
"io-github-br0ski777-vector-search": {
"url": "https://vector-search.api.klymax402.com/mcp"
}
}
}Documentation
View on GitHubFrom the project's GitHub README.
Vector Search API
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
| Tool | Method | Path | Price | Description |
|---|---|---|---|---|
data_vector_search | POST | /api/search | $0.012 | Store 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
| 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') |
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.
- Catalog: https://klymax402.com/llms.txt
- Full API reference: https://klymax402.com/llms-full.txt
- Live stats: https://klymax402.com/stats
License
MIT
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