# Vector Search

> Use this tool when you need to efficiently retrieve semantically similar documents based on their vector representations. It solves problems related to information retrieval, document search, and text similarity analysis by utilizing TF-IDF weighting and cosine similarity scoring. The tool takes in vectorized document queries as input and returns a list of relevant documents as output, making it ideal for applications requiring fast and accurate semantic search capabilities.

Canonical page: https://skillsregistry.net/skills/br0ski777-vector-search  
JSON: https://api.skillsregistry.net/v1/skills/br0ski777-vector-search

## Description

This MCP server provides in-memory vector search using TF-IDF weighting and cosine similarity scoring for semantic document retrieval. It is deployed as a hosted SSE endpoint on Railway and uses the x402 micropayment protocol for per-call billing. Source code is available at github.com/Br0ski777/vector-search-x402.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** version-control
- **Updated:** 2026-05-18

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/br0ski777-vector-search)
- **Repository:** <https://github.com/br0ski777/vector-search-x402>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "br0ski777-vector-search"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/br0ski777-vector-search` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/br0ski777-vector-search/pull`

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