# windai-mcp

> Use this tool when you need to assess wind resources for any location on Earth, solving problems related to renewable energy planning and optimization. The WindAI MCP Server provides AI-powered analysis, taking location data as input and outputting detailed wind resource assessments. It is ideal for use in contexts such as wind farm planning, energy production forecasting, and environmental impact studies.

Canonical page: https://skillsregistry.net/skills/umedpaliwal-windai-mcp  
JSON: https://api.skillsregistry.net/v1/skills/umedpaliwal-windai-mcp

## Description

WindAI MCP Server — AI-powered wind resource assessment for any location on Earth.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** maps-location
- **Updated:** 2026-09-02

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/dg3fbmgjkm)
- **Repository:** <https://github.com/umedpaliwal/windai-mcp>

## 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": "umedpaliwal-windai-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/umedpaliwal-windai-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/umedpaliwal-windai-mcp/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