# MapBiomas Soil MCP

> MapBiomas Soil MCP — vitoreduardolimakenor-soil-pipeline-mcp. Use this tool when you need to analyze and process large-scale soil data without manual downloads, enabling efficient querying, monitoring, and insights generation for national maps. It solves problems related to soil data management, processing, and visualization, providing a streamlined interface for inputs such as recipe configurations and outputs like processed data and results. Ideal for use cases involving Earth Engine processing, task monitoring, and result interpretation.

Canonical page: https://skillsregistry.net/skills/vitoreduardolimakenor-soil-pipeline-mcp  
JSON: https://api.skillsregistry.net/v1/skills/vitoreduardolimakenor-soil-pipeline-mcp

## Description

Enables querying soil data, planning and executing Earth Engine processing recipes, monitoring tasks, and answering questions about results without downloading national maps.

## Trust

- **Trust score (0–1):** 0.67
- **Verification tier:** scanned
- **Last scanned:** 2026-08-29

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** monitoring
- **Updated:** 2026-08-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/cthnspkrog)
- **Repository:** <https://github.com/VitorEduardoLimaKenor/soil-pipeline-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": "vitoreduardolimakenor-soil-pipeline-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/vitoreduardolimakenor-soil-pipeline-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/vitoreduardolimakenor-soil-pipeline-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