# Forest Fire Visualization MCP Server

> Use this tool when you need to visualize and analyze forest fire data, as it collects and processes occurrence information to provide regional fire risk analysis and map visualizations, solving problems related to fire monitoring and prevention. It takes in fire occurrence data as input and outputs interactive maps and risk assessments, making it useful for emergency responders, researchers, and environmental agencies. Ideal for use in wildfire-prone areas, this tool provides critical insights for informed decision-making.

Canonical page: https://skillsregistry.net/skills/daniel8824-del-forest-fire-mcp  
JSON: https://api.skillsregistry.net/v1/skills/daniel8824-del-forest-fire-mcp

## Description

A Python-based MCP server that collects, analyzes, and visualizes forest fire occurrence data on maps, allowing users to access regional fire information, risk analysis, and map visualizations.

## Trust

- **Trust score (0–1):** 0.96
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** maps-location
- **Updated:** 2026-09-28

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/idvreiu76f)
- **Repository:** <https://github.com/daniel8824-del/forest-fire-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": "daniel8824-del-forest-fire-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/daniel8824-del-forest-fire-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/daniel8824-del-forest-fire-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