# mcp-everything-search

> Use this tool when you need to rapidly search and analyze files on a Windows system, providing AI models with instant access to file information and disk usage statistics. It solves problems related to slow file searching and limited system insights, enabling use cases like data retrieval and statistical analysis. Ideal for integrating with AI models like Claude, GPT, and Gemini, it accepts search queries as input and returns relevant file data and analytics as output.

Canonical page: https://skillsregistry.net/skills/guodaxia9527-mcp-everything-search  
JSON: https://api.skillsregistry.net/v1/skills/guodaxia9527-mcp-everything-search

## Description

A high-performance Model Context Protocol (MCP) server built for Windows. Leveraging the native Everything SDK, it provides AI models (like Claude, GPT, Gemini) with millisecond-speed file searching, statistical analysis, and disk usage insights.

## Trust

- **Trust score (0–1):** 0.87
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** search
- **Updated:** 2026-09-19

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/tfickvqsfp)
- **Repository:** <https://github.com/guodaxia9527/mcp-everything-search>

## 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": "guodaxia9527-mcp-everything-search"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/guodaxia9527-mcp-everything-search` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/guodaxia9527-mcp-everything-search/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt